Keywords

Jerry Jao, Employ, Lever, JazzHR, Pillar, interview intelligence, screening companion, talent acquisition, candidate experience, AI bias, responsible AI, IBM, deepfakes, candidate fraud, AI literacy, two-sided marketplace, organizational design, hiring technology

Takeaways

• Jerry's background in AI-powered personalization at Retention Science informs his approach at Employ, viewing both job seekers and hiring managers as people deserving a more thoughtful, personalized process

• Employ processed nearly 100 million applications last year, with some roles receiving two to three thousand submissions, making meaningful evaluation a serious operational challenge

• Pillar's interview and screening companions are being integrated platform-wide to improve TA accuracy and give recruiters measurable time back in their day

• Responsible AI is a strategic priority, with IBM as a thought partner on model bias, hallucinations, and protecting candidate data at scale

• Candidate fraud, including deepfakes and multiple identity submissions, is an emerging risk Employ is working to detect earlier in the funnel

• AI-optimized resumes are eroding the signal value of traditional screening, making interview intelligence increasingly critical

Quotes

• "What I'm most excited about is creating a more effective process for people to provide for their loved ones by getting to their dream jobs."

• "We want to help our TA team get home a little sooner, or take a 30-minute mental break if AI can help get that time back in their day."

• "Hiring managers are telling us people sound incredibly amazing, but once they get on the call, it's a little different."

• "We're all people at the end of the day, so how do we personalize the experience so no one feels overlooked?"

• "It's almost as big a change as when the internet first arrived. We're in a very uncertain and unprecedented time."

Chapters

00:02 Welcome and introductions

02:03 From consumer personalization to talent acquisition

04:55 Building a human-centered hiring marketplace

07:16 AI on both sides: the cat-and-mouse dynamic in recruiting

09:24 Restructuring Employ for agility and accountability

14:12 Screening companion, talent fit, and processing 100 million applications

20:40 Candidate fraud, deepfakes, and emerging hiring risks

22:07 Responsible AI and the IBM partnership

30:38 AI literacy in job descriptions and skills assessment

34:54 Jerry's new podcast and the future of TA storytelling

39:02 Navigating workforce uncertainty in the AI era

41:12 Closing reflections and Employ research reports

Jerry Jao: https://www.linkedin.com/in/jerryjao

Employ: http://www.employinc.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords 

Paul Rubenstein, Visier, people analytics, workforce planning, CHRO, human-machine efficiency frontier, ROI curve, humanity index, agentic AI, MCP server, intelligent service delivery, governance, data strategy, organizational design, courage gap, talent strategy, future of work

Takeaways 

• CHROs should track three curves: the human-machine efficiency frontier, the ROI curve on AI investments, and a humanity index covering talent density, engagement, and culture. 

• Most organizations are stuck in the "gym membership phase" — distributing AI tools without redesigning work — and real returns require intentional deconstruction and reassembly of jobs. 

• The courage gap is real: employees need to see self-disrupting behaviors modeled and rewarded before they willingly give up tacit knowledge to train agents. 

• MCP servers enable systems-to-systems intelligence that can give managers contextual, proactive insights in the flow of their work — without them ever having to engage HR directly. 

• Workforce planning is entering a golden age, requiring continuous, real-time, multi-dimensional design that mirrors how finance operates with FP&A. 

• AI governance needs to shift from restricting data by default to securing personal accountability for use — otherwise AI answers will remain narrow and biased. 

• When all companies have access to the same agents, people and culture will again be the differentiator — making the humanity index a strategic, not just a moral, priority.

Quotes 

• "The floor for the tools we expect at work has just risen. AI is one." 

• "You can't lay off a hand or an arm to recover your technology investment." 

• "I want my workforce plan to be as easy as Google Maps — give me traffic updates and help me reroute." 

• "Sameness does not yield greatness in a talent strategy." 

• "Don't rely on your company for your career. You are responsible for staying relevant." 

• "Just because you can automate something doesn't mean you should."

Chapters

00:02 Welcome and introductions

00:53 Paul's career journey and obsession with HR's untapped potential

05:05 How AI is changing the analyst role and collapsing distance to insight

06:50 The three curves framework for CHROs navigating AI adoption

10:46 Strategic work planning vs. workforce planning and the agentic org chart

14:11 Manager evolution in a human-agent workforce

16:33 The gym membership phase and why job redesign is the real unlock

19:39 The courage gap and cultural conditions for AI adoption

23:29 Protecting durable human skills and doing the hard things

26:50 AI governance and the tension between data restriction and answer quality

31:38 MCP servers and the future of intelligent HR service delivery

38:54 Orchestration layers and proactive manager engagement

45:50 How analytics builds HR's strategic credibility

47:03 AI as first mate and the case for continuous workforce planning

51:52 Closing thoughts on staying human-centric and owning your career

Paul Rubenstein: https://www.linkedin.com/in/paulrubensteinhr

Visier: https://visier.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Charlene Li, Winning with AI, Katia Walsh, AI strategy, AI fluency, AI literacy, integrated intelligence, superhuman worker, workforce planning, reskilling, pilot purgatory, responsible AI, ethical AI, governance, human centricity, talent transformation, future of work, organizational disruption, values-based AI, co-intelligence

Takeaways

• Lead with business strategy, not AI technology — the question is never "what can we do with AI?" but "how can AI help us accomplish what we're already trying to do?"

• AI fluency, not just literacy, is the goal — fluency means reaching for AI naturally, trusting it, and using it to learn how to use it better, like chopsticks becoming second nature

• Organizations stuck in pilot purgatory are procrastinating real decisions — pilots give everyone an excuse not to commit, and that dooms projects from the start

• Successful examples show a better path: use AI to raise workforce quality first, then expand customer value, then reinvent the business entirely

• Reskilling requires both organizational imagination and honest values — the IKEA story turned 8,500 displaced service reps into a $1B design business

• Integrated intelligence combines AI's speed and scale with uniquely human traits — empathy, judgment, intuition, self-reflection, and wisdom — to create superhuman capability

• AI fluency in hiring is shifting from a red flag to a baseline expectation — how candidates use AI reveals curiosity, creativity, and adaptability far better than traditional interviews

• Responsible AI governance done right isn't a compliance burden — a gold-standard internal policy means regulation becomes a checkbox, not a crisis

Quotes

• "You don't need an AI strategy — you already have a business strategy. Figure out what of your business strategy could really be impacted with AI."

• "Automating a broken process is the definition of madness. Because of AI, could we do this in a completely different way?"

• "AI can only be as creative as your questions are. It can only be as empathetic as you are."

• "We should stop doing pilots. It's just another way to procrastinate having to say yes or no."

• "The first thing they said was, we are not going to use AI to cut people. That is not the intent going in."

• "You aim for a higher level than any regulation would ever want. You go for the gold standard and whatever they ask of you, of course you do those things."

Chapters

00:03 Welcome and guest introduction

01:27 Catching up since Fall 2024 and the impetus for Winning with AI

02:45 The 90-day framework and leading with business strategy

05:46 Reimagining work versus automating broken processes

09:22 AI fluency as an organizational imperative

14:06 Making AI practice habitual and learning in community

17:54 Embedding AI in the flow of work and escaping pilot purgatory

20:07 Workforce reinvestment and a recent case study

26:35 Reskilling, redeployment, and the IKEA story

29:54 Getting C-suite and boards to embrace a human-centric approach

33:38 Starting with customers and thinking beyond efficiency

38:30 Building AI fluency fast and making the investment

41:38 AI fluency in recruiting and hiring for AI capability

47:52 Integrated intelligence and the rise of the superhuman worker

50:42 From individual productivity to team and organizational impact

52:14 Values-based AI and imbuing organizational values into AI systems

55:53 Responsible and ethical AI as a strategic advantage

59:38 Goldilocks governance and the 90-day blueprint

01:00:21 Closing thoughts and book information

Charlene Li: https://www.linkedin.com/in/charleneli

“Winning With AI”: https://winningwithaibook.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Oded Dubovsky, STRAIX, AI strategy, AI execution, AI adoption, cognitive computing, computer vision, IBM Research, Haifa Lab, Watson, automation, generative AI, vibe coding, AI-assisted coding, responsible AI, human centricity, AI readiness, orchestration, innovation, shadow AI

Takeaways

• Only about 5% of companies successfully adopt AI — most struggle with where to start, what tools to use, and how to build the right foundation before scaling

• AI is the "penthouse" built on top of decades of IT, software engineering, and automation experience — that foundational knowledge remains critical

• The human role is shifting from execution to orchestration and architecture — developers and knowledge workers are becoming "team leads" directing AI agents

• Responsible AI development means thinking through security, data, scalability, and governance from the start — not as an afterthought

• Slowing down to think carefully before prompting or building — echoing Einstein's 55/5 rule — leads to better, more scalable outcomes

• Early cognitive computing projects at IBM (food recognition, augmented reality for remote guidance) were ahead of their time, foreshadowing capabilities now taken for granted

• Human originality and the ability to generate truly novel ideas remain a distinctly human trait that AI has not replicated

Quotes

• "AI is kind of the top level, like the penthouse on top of all of that."

• "95% are just saying we need AI — they kind of don't know how to absorb that, how to start using it."

• "Once I crossed the line, I couldn't go back."

• "Think about it — you just got a promotion. You're a team lead now. You don't micromanage. You give them the bigger picture."

• "If I had an hour to solve a problem, I'd spend 55 minutes thinking about the problem and five minutes thinking about the solution." — Einstein, as quoted by Oded

• "Slow down to speed up."

Chapters

00:02 Welcome and introductions

01:04 Oded's background and career journey from IBM to Intel to STRAIX

08:08 Early cognitive computing at IBM — the Watson era and the "What Did I Eat?" project

13:01 From research to product — augmented reality, 3D cameras, and lessons learned

17:54 How AI adoption is accelerating and compressing what once took a decade

20:14 Why 95% of organizations struggle to execute on AI

24:54 How STRAIX works — mapping pain points, building a heat map, and guiding implementation

29:47 Automation tools, vibe coding, and the value of foundational experience

33:13 Human readiness and the mindset shift required to embrace AI

37:22 AI agents, social networks, and the human as orchestrator

44:20 Responsible AI development — building with guardrails from the start

51:26 Asking better questions and thinking architecturally before building

53:31 Closing thoughts and how to connect with Oded

Oded Dubovsky: https://www.linkedin.com/in/odeddubovsky

STRAIX: www.straix.biz

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Jacob Bank, Relay.app, AI agents, agentic workflows, autonomous workers, workflow automation, small business, AI literacy, people management, Timeful, Google Calendar, Gmail, knowledge work, G&A, go-to-market, responsible AI, human-in-the-loop, SaaS evolution

Takeaways

• The right mental model for AI agents is employee management: give them a job description, set expectations, provide feedback, and apply the same code of conduct as any team member

• Everyone needs three AI tools: a chatbot for conversation, a copilot for real-time task delegation, and an autonomous agent platform for proactive, repeatable work

• Relay runs on 9 humans and ~60 AI agents — and Jacob sees a path to serving 100x more customers with roughly the same team size

• AI levels the playing field for small businesses, enabling work at a scale previously only achievable by much larger organizations

• Jacob's three-level delegation progression: tasks you already do, tasks you're capable of but never have time for, and tasks you'd otherwise hire an expert for

• AI literacy is not optional — it's becoming a baseline requirement for effective work, equivalent to basic computer literacy

Quotes

• "We're all managers now — that is the skill set we need."

• "If you have a job that is just to write the blog post about X, that job is not going to exist anymore."

• "It's not optional. This is going to be a requirement of being an effective worker in the future."

• "Whenever I have an AI agent doing a classification task, I always ask the AI to explain its rationale — because then you can correct it for next time."

• "At some point you'll cross this tipping point where you don't have to tell yourself to go use AI — it'll suck you in."

Chapters

00:02 Welcome and introductions

00:56 Jacob's origin story and agent-oriented programming

02:54 From Timeful to Google

04:41 Pre-LLM AI features in Gmail and Calendar

06:15 AI coworkers vs. productivity tool nudges

07:39 Early agent research and org disruption

09:24 Restructuring knowledge work

11:45 Evolving human roles and AI literacy

13:32 The social complexity of scheduling

15:16 Credentialed jobs at risk

17:24 AI leveling the playing field for small business

18:17 Inside Relay — 9 humans and 60 agents

19:41 The three-tier AI stack

22:38 Relay as intelligent workflow automation

23:42 SaaS selection in the agent era

26:47 Platform consolidation and SaaS business models

28:13 Deploying agents across G&A, GTM, and R&D

33:16 Agent collaboration and human oversight

34:21 When to build vs. buy

37:56 Three levels of AI delegation

39:50 Scaling AI readiness across organizations

42:22 Responsible AI and the employee management lens

44:14 Evaluating agents vs. testing software

45:51 The blast radius problem

48:09 Bias, coachability, and correcting agents

49:29 Closing advice — go one step further

50:45 What's next for Relay

Jacob Bank: https://www.linkedin.com/in/jacobbank

https://relay.app

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Hyperadaptive, AI native, AI transformation, support structures, AI activation hubs, AI leads, dynamic governance, systems thinking, durable skills, adjacent competencies, agentic workflows, responsible AI, triple bottom line, career lattice, organizational design, value streams, Melissa Reeve, Elevate Your AIQ

Takeaways

• Most AI transformations fail not because of technology, but because organizations underinvest in support structures — from AI councils to activation hubs to frontline AI leads

• Becoming AI native is a gradual five-stage journey: foundation, workflow integration, agentic AI, scaling agents, and full hyper-adaptivity

• The bifurcation problem is real: a small percentage self-direct their AI learning while the majority are left behind without programmatic support

• Individual productivity gains are a vanity metric — what matters is whether AI unlocks new organizational capabilities and a more ambitious mission

• The shift for workers is from doing the task to building, monitoring, and maintaining the AI that does it — durable skills like systems thinking are central to that transition

• Adjacent competencies unlocked by AI are where breakthrough innovation happens, especially at the intersection of previously siloed domains

• Responsible AI and the triple bottom line — people, profit, and planet — must be woven into AI native organizations from the start

Quotes

• "A piano is easy to use — you can dink around on the keys all day, but it's not really easy to learn."

• "You can't get 21st century results with the 20th century operating system."

• "With great power comes great responsibility — and I don't think there's enough attention being put to the implications of AI."

• "The shift is from creating to building, monitoring, or maintaining — and there will always be room for the artisans."

• "AI changes who can do what — and that's where the innovation is, at the overlay of disciplines."

Chapters

00:02 Welcome and introductions 

01:17 Melissa's non-linear path and the origins of Hyperadaptive 

03:49 Systems thinking, transferable skills, and shared career philosophies 

05:13 Unpacking AI native and what it means for organizational design 

07:53 Why large enterprises are struggling and the aircraft carrier analogy 

09:21 AI maturity, readiness, and knowing where to draw the line 

11:14 The biggest mistake: neglecting human support structures 

13:57 AI activation hubs, AI leads, and dynamic governance 

19:14 Centralized vs. functional governance layers 

23:14 Where most organizations stand in early 2026 

26:16 Individual productivity as a vanity metric 

28:02 Unlocking organizational potential beyond current capabilities 

31:22 Adjacent competencies, durable skills, and the future of careers 

37:48 Systems thinking and redesigning work 

40:05 Career lattices, value streams, and Unilever's talent model 

43:10 AI governance, responsible AI, and the triple bottom line 

50:48 Melissa's book release details

Melissa Reeve: https://www.linkedin.com/in/melissamreeve

Hyperadaptive Solutions: https://hyperadaptive.solutions

For advisory and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Jonathan Aberman, Hupside, OIQ, Original Intelligence Quotient, AI readiness, human originality, talent transformation, workforce design, higher education, venture capital, AI augmentation, digital credentials, collective intelligence, responsible AI, human-AI symbiosis

Takeaways

• Hupside's OIQ objectively measures human originality against AI output, helping organizations identify who to develop, elevate, or support through AI transformation

• AI creates a self-reinforcing feedback loop that debilitates when misused — but as a tool, it can powerfully accelerate human creativity

• Originality equals novelty plus salience; AI can generate novelty, but humans remain essential for determining what's meaningful

• Higher education's real challenge isn't cheating prevention — it's teaching students to reason well with AI, then measuring output quality

• Misaligning high-OIQ talent with constrained roles leaves value on the table; matching autonomy to originality profiles is a key workforce design opportunity

• The greatest long-term AI risk may be whether rising capability gradually excludes people from competing as knowledge workers

• OIQ and AIQ scores are dynamic and improvable — making them well-suited for portable digital credential profiles

Quotes

• "AI has a couple of limitations that make it different from every tool humans ever invented — it creates a self-reinforcing loop that can cause debilitation if not used properly."

• "We're the umpire in a baseball game. We're not the players — you and your listeners are the players."

• "AI is not a cheating problem, it's an education problem."

• "Originality is novelty plus salience. As long as humans are the ones consuming, AI will always be at best a lieutenant."

• "The more we [flood] society with sameness, the more people who stand out are going to be important."

• "I'm not worried about whether AI becomes sentient. I'm more worried about whether it raises the bar and starts to exclude people."

Chapters

00:02 Welcome and introductions 

02:58 The founding of Hupside and the OIQ origin story 

05:35 AI readiness as a human potential problem 

07:53 OIQ in higher education and rethinking assessment 

09:11 K-12 considerations and bias mitigation 

11:20 VC and portfolio applications of OIQ 

15:11 Embedding OIQ into the talent lifecycle 

19:56 Autonomy, role design, and workforce orchestration 

24:42 Higher education, authenticity, and the value of originality 

27:04 Innovation management and organizational barriers to AI adoption 

34:52 Short-termism, Silicon Valley monoculture, and pushing back 

39:25 Can LLMs become truly original? Shared novelty vs. human originality 

43:20 Collective intelligence and the wisdom of crowds 

48:53 Digital credentials, OIQ in talent profiles, and data ownership 

54:43 What's next for Hupside and closing thoughts

Jonathan Aberman: https://www.linkedin.com/in/jonathanaberman

Hupside: hupside.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠
Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords 

Juan Garcia, Tuio, insurtech, digital insurance, personal lines, Spain, AI strategy, claims automation, Watson, human in the loop, AI literacy, responsible AI, subscription insurance, underwriting, organizational transformation, vertical AI, bottom-up innovation

Takeaways

• Tuio identified a digitally-native consumer segment structurally unprofitable for traditional insurers and built a model around serving them through simplicity and transparency

• Most AI pilots focus on the wrong 10%: cost-to-serve efficiencies. Real value lies in improving decisions across marketing and claims, which represent ~85% of an insurer's cost base

• Watson processes multimodal inputs and generates next-best-action suggestions with confidence scores — routing complex ones to human reviewers

• Tuio never automates negative customer decisions — not just due to EU regulation, but because human empathy is irreplaceable in those moments

• By subsidizing any AI tools employees want to explore, Tuio unlocked bottom-up innovation — including a veterinarian who independently proto-built Watson's logic for pet health claims

• The real barrier to enterprise AI transformation is organizational courage: reworking processes and structures around AI requires strong leadership

Quotes

• "AI is something that makes you rethink the way you do your whatever you do — and that's going to be different industry per industry, even company per company."

• "We switched from chasing cost-to-serve efficiencies to using AI to make better decisions — growing efficiently, underwriting smarter, and managing claims more effectively."

• "We will never automate negative decisions. If you start from the standpoint that your customers are your most valuable resource, you want to give them the most humane treatment you can."

• "If you don't give people these tools, you'll miss all the bottom-up ideas from the people actually in the trenches every day."

• "Even if you can build it, it doesn't mean you should. Just because AI can do something doesn't mean you should deploy it there."

Chapters

00:02 Welcome and introductions 

00:44 Juan's background: from telecom engineer to insurtech co-founder 

03:31 Horizontal vs. vertical AI value — where the real opportunity lies 

06:41 Tuio's target market and the underserved digitally-native consumer 

12:54 Rethinking insurance: digital simplicity as competitive advantage 

16:03 Tuio's AI evolution: from chatbot to decision intelligence 

20:54 Watson: Tuio's AI claims agent and the shift to next-best-action 

23:24 Human in the loop: why some decisions will never be automated 

28:53 Building AI literacy through empowerment, not training mandates 

32:52 Bottom-up innovation and the veterinarian who built Watson's prototype 

40:31 AI readiness, responsible design, and knowing what not to build 

45:15 Organizational courage and why AI transformation is harder than those before it 

53:30 Closing reflections and what's next for Tuio

Juan Garcia: https://www.linkedin.com/in/juanga2/

Tuio: https://tuio.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Russ Fradin, Larridin, AI ROI, AI readiness, AI maturity, workforce transformation, CIO strategy, CHRO strategy, CFO decision-making, productivity measurement, high-agency professionals, AI adoption, responsible AI, enterprise AI, organizational change

Takeaways

• AI adoption without measurement leads to experimentation without accountability.

• CIOs, CFOs, and CHROs need visibility into what tools are actually being used—and whether they drive real productivity.

• The future of knowledge work is humans working with AI tools alongside agents.

• High-agency professionals who embrace AI will dramatically amplify their output and career trajectory.

• Organizations must move beyond individual productivity metrics toward team and enterprise-level effectiveness.

• Responsible AI adoption requires training, policy scaffolding, and clarity around secure, enterprise-grade usage.

• Companies that reinvest AI-driven productivity into growth will outperform those focused solely on short-term margin gains.

Quotes

• “You can’t possibly understand the ROI of these tools without understanding what’s being used in your organization.”

• “Having great technology is necessary, but not sufficient to drive change.”

• “The future of work is humans using AI tools, working alongside agents.”

• “There’s no such thing as a knowledge worker five years from today who isn’t using AI in some part of their job.”

• “We’re effectively redefining what it takes to succeed in a lot of these roles—in real time.”

• “The companies that don’t partner with their employees on this transformation will get left behind.”

Chapters

00:02 Welcome and Introduction

00:31 Russ’s Background and the Vision Behind Larridin

01:32 Why AI Is a Generational Technology Shift

03:34 The Measurement Gap in Enterprise AI Adoption

06:17 Workforce Anxiety and AI Upskilling

10:33 The ROI Question and Productivity Metrics

15:10 Global Talent, Competition, and AI Parallels

20:17 Responsible AI and Security Considerations

26:20 Building the Scaffolding for Adoption

30:48 Understanding What “Great” Looks Like

34:55 Who Captures the Productivity Gains?

40:22 The High-Agency Advantage in the AI Era

46:09 Why Smart Companies Invest in Their People

52:04 What’s Next for Larridin

53:09 Closing Remarks

Russ Fradin: https://www.linkedin.com/in/rfradin

Larridin: https://larridin.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Stephen Messer, Collective[i], Intelligence.com, collective intelligence, economic foundation model, relationship graphs, trust networks, contextual AI, sales productivity, forecasting, CRM transformation, go-to-market strategy, weak ties, network intelligence, AI agents, decision-making

Takeaways

• Collective intelligence enables AI to model real-world business systems, not just generate language or automate workflows.

• Context — including relationships, timing, incentives, and market conditions — is the missing ingredient in most AI-driven decision-making.

• Traditional SaaS stacks create “silos of intelligence,” limiting visibility and reducing the effectiveness of AI tools layered on top.

• Relationship graphs built from verified interactions unlock faster, higher-trust introductions and better business outcomes.

• Trust acts as an accelerator in commerce, reducing friction and enabling decisions at “warp speed.”

• Economic foundation models can forecast deal outcomes and market shifts by observing patterns across organizations.

• AI should remove internal friction so humans can focus on value creation, not administrative workflows.

• The future of work depends on combining contextual intelligence with trusted human networks.

Quotes

• “To the man with a hammer, the world looks like a nail.”

• “You’re not modeling words — you’re modeling a system.”

• “If I don’t understand the context, I can’t understand the outcome.”

• “Trust enables transactions at warp speed.”

• “Most AI today is predicting the next best word — not the next best decision.”

• “The friction to leverage your own network is far too high.”

Chapters

00:01 Introduction and Stephen’s Entrepreneurial Journey

00:40 Founding Collective[i] and the Vision Behind It

02:22 Replacing the Traditional Sales Stack with Contextual AI

05:46 Why Context Matters More Than Prompt Engineering

09:18 Systems of Record vs. Systems of Understanding

16:01 The Limits of LinkedIn and Relationship Context

23:24 Introducing Intelligence.com and Verified Networks

36:39 The Origins of Collective Intelligence and Economic Modeling

48:20 Trust Networks, Hiring, and Weak Ties

55:52 Forecast Series and the Power of Long-Form Dialogue

1:00:58 Closing Thoughts and What’s Next

Stephen Messer: https://www.linkedin.com/in/stephenmesser

Collective[i]: https://collectivei.com/

Intelligence.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Dave Vu, Ribbon.ai, AI interviews, high-volume hiring, candidate experience, responsible AI, human-in-the-loop, talent acquisition, hiring automation, bias mitigation, AI regulation, recruiter efficiency, quality of hire, generative AI

Takeaways

• Application volume has grown exponentially while recruiter headcount has remained relatively flat, creating a widening efficiency gap.

• AI interviews can reduce screening time by 50% or more while improving consistency and fairness.

• Candidate experience improves when applicants receive timely engagement, flexibility, and meaningful feedback.

• Human-in-the-loop design ensures AI handles repetitive tasks while recruiters retain decision-making authority.

• Transparency about AI usage builds trust and increases candidate adoption.

• Regulatory clarity will accelerate enterprise adoption of AI in hiring.

• Responsible AI implementation requires balancing innovation with bias mitigation and compliance guardrails.

• Generative AI advancements are reshaping not only hiring, but content creation and digital trust more broadly.

Quotes

• “Our long-term mission is to hire within 24 hours and make hiring faster and fairer.”

• “Human-centricity doesn’t equate to anti-automation.”

• “The recruiter and hiring manager are always in the driver’s seat.”

• “It’s not about replacing humans—it’s about amplifying their capacity.”

• “Great candidate experience comes down to respect for their time.”

• “Regulations create certainty—and certainty accelerates adoption.”

Chapters

00:02 Introduction and Dave’s career journey in talent

02:55 Scaling an AI startup and identifying hiring challenges

05:02 The high-volume hiring problem and Ribbon’s mission

10:40 Designing a better candidate experience with AI

15:16 Rethinking resumes and screening inefficiencies

22:41 Human-in-the-loop and responsible AI principles

24:40 Regulation, transparency, and enterprise adoption

28:57 Candidate acceptance and AI interview adoption trends

34:28 Integration with ATS platforms and workflow evolution

43:01 Personal reflections on generative AI and digital trust

49:29 AI literacy, workforce disruption, and the future of hiring

Dave Vu: https://www.linkedin.com/in/dave-vu

Ribbon: https://ribbon.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Tim Borys, Fresh Group, workplace wellbeing, human performance, burnout, executive coaching, leadership, adaptability, AI and work, human-centric AI, WRKdefined Podcast Network, Elevate Your AIQ

Takeaways

• Sustainable performance requires focusing on human fundamentals like rest, recovery, and mindset

• High-performing corporate cultures often neglect wellbeing until burnout occurs

• Adaptability and learning are the most critical skills for thriving amid AI-driven change

• Leadership and communication skills will be essential for managing both people and AI agents

• Human performance, leadership, and business strategy must be addressed together

• AI should augment—not replace—human agency and critical thinking

Quotes

• “Corporate high performers seem to think the rules of human performance don’t apply to them.”

• “Work sucks for a lot of people—and it doesn’t have to.”

• “Every human has a human operating system, and most people never optimize it.”

• “Adaptability is the number one human skill for thriving.”

• “As technology becomes more powerful, the human side matters even more.”
  

Chapters

00:02 Welcome and introduction

00:43 Tim’s journey from elite athletics to executive coaching

02:39 Applying human performance principles to corporate work

04:32 Burnout, sleep, and sustainable performance

07:22 Human potential and wellbeing at work

09:05 The human operating system

12:06 Human-centric AI and the cost of efficiency

14:12 Adaptability, learning, and future skills

18:06 Fear, uncertainty, and career resilience

23:10 Leadership skills for managing AI agents

29:49 Performance-managing AI and responsible use

36:29 Frontline leaders vs. executive perspectives

43:52 Mindset, perception, and human agency

47:27 Personal AI tools and experimentation

51:30 The Working Well podcast and closing

Tim Borys: https://timborys.com/

Working Well podcast: https://wrkdefined.com/podcast/the-working-well-podcast

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Lance Thompson, VIVI, SAVI, hospitality tech, voice AI, multilingual support, hotel operations, HR automation, guest experience, AI adoption, Microsoft Azure, Kinetic Solutions Group, Four Seasons, Vail Resorts, Aspen Hospitality, AI in travel, shadow AI, responsible AI, agentic search, reservations automation, guest personalization

Takeaways

• Lance's career spans luxury hospitality, including Four Seasons and Vail Resorts, before shifting into tech with the founding of SAVI, now VIVI

• VIVI is leveraging AI voice agents to support hotel operations, from answering phones to making reservations and handling HR inquiries

• Multilingual capabilities are critical in hospitality; VIVI agents can fluently switch between languages in real time

• Lance emphasizes the importance of consistency in service delivery — AI can ensure high-quality, brand-aligned experiences across time zones and locations

• Unlike traditional decision-tree systems, VIVI’s tools rely on conversational AI that listens, adapts, and can be interrupted mid-sentence

• Shadow AI poses risks for companies — Lance urges leaders to develop clear internal policies for responsible use and governance

• VIVI's architecture is designed with data privacy and security in mind, with each client having its own isolated knowledge base

• The future of hospitality AI lies in scalable, personalized tools that blend human empathy with machine precision
  

Quotes

• “I wanted to be in a space where I could help people have a better experience in life — and hospitality gave me that.”

• “If it can’t be interrupted, it’s not a conversation. And that’s what real guest service is about.”

• “We don’t want to replace Janet in Reservations — we want to scale her.”

• “Guests don’t want a link. They want an answer — fast, accurate, and in their language.”

• “People aren’t afraid of AI. They’re asking when they can start using it to be more effective at their jobs.”

• “We’re not building a static product. As the models improve, our tools do too.”
  

Chapters

00:00 - Intro and background from Carmel to Colorado

02:47 - Lance’s early passion for hospitality

05:09 - Discovering the limits of legacy systems

07:10 - The spark behind founding SAVI (now VIVI)

08:48 - Early demos, use cases, and multilingual potential

11:36 - Why real conversational AI matters

14:59 - Shadow AI and responsible adoption

17:54 - Building secure, client-specific AI agents

23:33 - Creating community through consistent service

26:39 - Managing real-time updates and seasonal accuracy

29:39 - Rethinking apps and improving discoverability

32:19 - The magic of humanlike conversations

36:02 - Delivering 5-star experiences through AI

39:30 - Personalizing brand voice (yes, even “absolutely”)

41:09 - Customizing user experience in real-time

43:03 - Transparency, trust, and guest empowerment

46:25 - What’s next for VIVI and hospitality AI

48:00 - Expanding into HR, golf, and reconciliation tools

51:06 - The travel planning use case

53:19 - New challenges in AI-driven SEO

53:23 - Final reflections and what’s ahead

Lance Thompson: https://www.linkedin.com/in/lance-thompson-92a5476

VIVI: http://www.vivi.bot/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Vijay Swami, Draup, AI in HR, People Analytics, Strategic Workforce Planning, verification skills, ethical AI, talent intelligence, agentic AI, skills-based hiring, cloud data, explainability, trust, synthetic data, digital twins, ETTER, Curie, job displacement, augmented intelligence, transparency

Takeaways

• AI's value in HR lies in sense-making from complex and unstructured data, not just simplifying workflows.

• Verification skills—like content and narrative validation—are emerging as critical in a world flooded with AI-generated data.

• Draup’s AI agent Curie supports HR and analytics professionals with leadership-ready narratives and scenario planning.

• The platform's ETTER model goes beyond job descriptions to assess real work through contracts, SLAs, and KPIs.

• Transparency and traceability are foundational to building trust in AI systems; Draup compares its models against industry benchmarks.

• Ethical AI practices include open documentation, interpretability, and empowering analysts to correct or clarify information.

• AI should not be viewed solely as a job killer; clear, specific skills definitions in job postings can increase hiring and help target investments.

• True transformation requires shifting from jobs to workflows and task orchestration, blending human effort, AI agents, and automation.

Quotes

• “We want to tell the story—not just show the data—to help people analytics become a leadership engine.”

• “Verification skills are the next battery of capabilities organizations must build for a trustworthy enterprise.”

• “Transparency is about giving customers the right to know—even if they don’t ask.”

• “HR has the opportunity to become heroes in this AI wave by unlocking the true nature of work.”

• “We should be therapists for data anxiety—helping organizations see what’s real versus what’s a myth.”

• “I’m a net AI job creator guy—because there’s no shortage of work, just a need to match skills and workflows more intelligently.”
  

Chapters

00:05 - Introduction and Vijay’s background

00:57 - From forecasting analyst to AI-powered platforms

03:18 - Rethinking labor intelligence beyond job descriptions

05:39 - Building a sense-making engine from complex data

07:42 - Storytelling, context, and executive alignment

11:15 - The rise of verification skills

14:04 - Creating a trusted and transparent AI ecosystem

19:31 - Unlocking the true nature of work through ETTER

22:44 - Ethical AI and human-centric design

32:19 - How data becomes a therapeutic tool

35:14 - AI’s real impact on jobs and skills demand

45:25 - Strategic work planning beyond job roles

49:19 - Optimism, augmentation, and future-proofing teams

50:34 - Closing thoughts and appreciation

Vijay Swami: https://www.linkedin.com/in/vijay-swaminathan-a44101/

Draup: https://draup.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

AIQ, AI literacy, responsible AI, human-centric design, talent transformation, skills-based hiring, human potential, CHRO of the future, work redesign, education reform, podcasting, Substack, transformation leaders, automation strategy, AI readiness, AI ethics, trust, transparency, fairness, lifelong learning, community, AI-powered workforce

Takeaways

• Podcasting is a powerful outlet for exploring curiosity, storytelling, and continuous learning—especially for neurodivergent thinkers.

• Human-centric AI readiness is not just about tools or tech—it’s about mindset, adaptability, and lifelong learning.

• AIQ exists on three levels: individual, team, and organizational—each requiring a blend of skills, tools, and ethical judgment.

• Responsible AI is central to modern transformation—touching on transparency, fairness, ethics, and explainability.

• CHROs and people leaders have dual responsibilities as strategic architects of work and catalysts for responsible innovation.

• Hiring for skills and potential—rather than pedigree—is crucial to unlocking hidden talent and countering bias.

• Education and talent development must evolve to equip students and workers with the durable skills of the AI-powered future.

• Communities of practice and peer generosity are vital to collective learning and resilience in this era of rapid change.

Quotes

• “Use AI where you should, not wherever you can.”

• “We’ve always adapted to new technologies—this time is no different.”

• “Human-centricity and human potential are key overarching themes of this show, and of the future of work.”

• “AIQ isn’t just about literacy—it’s about readiness, judgment, and mindset.”

• “If you are a DEI advocate, you are now a responsible AI advocate.”

• “You can control your own destiny—you’re capable of more than you think.”

Chapters

00:00 Welcome and Gratitude for Episode 100

00:50 Human-Centric AI and the Purpose of the Show

02:32 Authenticity, Creativity, and Focus

04:35 My Background: Corporate to Independent

07:18 Early Exposure to AI at IBM and Personal Stakes

09:55 Start with Processes and Business Challenges, Not Tech

11:48 Three Levels of AIQ: Individual, Team, Org

13:45 Beyond Prompting: Augmenting Capabilities

15:20 Responsible AI: Use and Design

17:30 The Role of Trust, Transparency, and Fairness

19:50 DEI and Responsible AI Are Inseparable

21:10 Skills-Based Hiring and Hidden Potential

23:00 Designing Work for Human + AI Partnership

25:40 Lifelong Learning and the Future of Education

27:20 CHROs as Architects and Innovation Catalysts

29:30 Offense and Defense in Responsible Innovation

31:00 A Call to Action for Listeners and the Community

32:10 What’s Next: Live Shows, Events, Writing, and Community

33:20 Closing Gratitude and Future Outlook

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Ross Dawson, Humans + AI, AI roadmap, ThoughtWeaver, AI teaming, digital twins, augmented thinking, talent marketplaces, future of work, systems thinking, AI in organizations, AI in education, trust in AI, AI-enabled teams, cognitive diversity, latent talent, fluid talent, organizational design

Takeaways

• The “Humans + AI” framework centers on complementarity, not substitution — AI should augment and elevate human potential.

• AI maturity is not just technical — it requires cultural readiness, mindset shifts, and systems-level thinking.

• Trust in AI must be calibrated; both over-trusting and under-trusting limit value creation.

• AI-enabled teams will rely on clear role design, thoughtful delegation of decision rights, and frameworks for collaborative intelligence.

• Digital twins and AI agents offer different organizational advantages — one mimics individuals, the other scales domain expertise.

• Organizations must reimagine work as networks of capabilities, not boxes of job descriptions.

• Talent marketplaces are an early expression of fluid workforce models but require intentional design and leadership buy-in.

• The most human-centric organizations will be best positioned to attract talent and thrive in the AI era.

Quotes

• “AI should always be a complement to humans — not a substitute.”

• “We live in a humans + AI world already. The question is how we shape it.”

• “Mindset really frames how much value we can get from AI — individually and societally.”

• “You know more than you can tell. That gap between tacit knowledge and what AI can access is where humans still shine.”

• “Start with a vision — not a headcount reduction. Ask what kind of organization you want to become.”

• “We can use AI not just to apply existing capabilities but to uncover and expand them.”

Chapters

00:00 - Welcome and Ross Dawson’s introduction

01:10 - From futurism to Humans + AI: key focus areas

03:30 - How AI is shifting public curiosity and mindset

06:00 - Systems-level thinking and responsible AI use

08:20 - AI in education and enterprise transformation

11:10 - The rise of AI-augmented thinking

14:00 - Calibrating trust in AI and human roles in teams

17:00 - Designing humans + AI teaming frameworks

20:30 - Delegation models and decision architecture

23:20 - Digital twins vs synthetic AI agents

26:00 - The value of tacit knowledge and cognitive diversity

30:00 - Empowering individuals amidst career uncertainty

32:10 - Breaking out of job “boxes” with fluid talent models

35:00 - Talent marketplaces and barriers to adoption

38:00 - Human-centric leadership in AI-powered transformation

41:00 - Strategic roadmaps and vision-led change

45:30 - Ross’s personal AI tools and experiments

52:00 - Final thoughts on AI’s role in augmenting human creativity

Ross Dawson: https://www.linkedin.com/in/futuristkeynotespeaker

Humans + AI: https://humansplus.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Day of AI, MIT RAISE, responsible AI, AI literacy, K-12 education, student privacy, AI companions, Common Sense Media, AI policy, AI ethics, educational technology, AI curriculum, teacher training, creativity, critical thinking, digital natives, student agency, future of education, AI and the arts, cognitive offloading, generative AI, AI hallucinations, PISA 2029, AI festival

Takeaways

• Day of AI is equipping teachers, students, and families with tools and curricula to understand and use AI safely, ethically, and productively.

• AI literacy must start early and span disciplines; it’s not just for coders or computer science classes.

• Students are already interacting with AI — often without adults realizing it — including the widespread use of AI companions.

• A core focus of Day of AI is helping students develop a healthy skepticism of AI tools, rather than blind trust.

• Writing, critical thinking, and domain knowledge are essential guardrails as students begin to use AI more frequently.

• The AI Festival and student policy simulation initiatives give youth a voice in shaping the future of AI governance.

• AI presents real risks — from bias and hallucinations to cognitive offloading and emotional detachment — especially for children.

• Higher education and vocational programs are beginning to respond to AI, but many are still behind the curve.

Quotes

• “AI is more powerful than a car — and yet we’re throwing the keys to our kids without requiring any kind of driver’s ed.”

• “We want kids to be skeptical and savvy — not just passive consumers of AI.”

• “Students are already using AI companions, but most parents have no idea. That gap in awareness is dangerous.”

• “Writing is thinking. If we outsource writing, we risk outsourcing thought itself.”

• “The U.S. invented AI — but we risk falling behind on AI literacy if we don’t act now.”

• “Our goal isn’t to scare people. It’s to prepare them — and let young people lead where they’re ready.”

Chapters

00:00 - Welcome and Introduction to Jeff Riley

01:11 - From Commissioner to Day of AI

02:52 - MIT Partnership and the Day of AI Mission

04:13 - Global Reach and the Need for AI Literacy

06:37 - Resources and Curriculum for Educators

08:18 - Defining Responsible AI for Kids and Schools

11:00 - AI Companions and the Parent Awareness Gap

13:51 - Critical Thinking and Cognitive Offloading

16:30 - Student Data Privacy and Vendor Scrutiny

21:03 - Encouraging Creativity and the Arts with AI

24:28 - PISA’s New AI Literacy Test and National Readiness

30:45 - Staying Human in the Age of AI

34:32 - Higher Ed’s Slow Adoption of AI Literacy

39:22 - Surfing the AI Wave: Teacher Buy-In First

42:35 - Student Voice in AI Policy

46:24 - The Ethics of AI Use in Interviews and Assessments

53:25 - Creativity, No-Code Tools, and Future Skills

55:18 - Final Thoughts and Festival Info

Jeff Riley: https://www.linkedin.com/in/jeffrey-c-riley-a110608b

Day of AI: https://dayofai.org

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

AI literacy, Gen Z, future of work, healthcare AI, trusted data, responsible AI, education, automation, disconnection, skills, strategy, adoption, social media, transformation

Takeaways

• Gen Z’s experience with AI is shaped by a rapid-fire sequence of disruptions: COVID, remote learning, and now Gen AI

• Both podcast and book You Teach the Machines serve as a “time capsule” for capturing AI’s societal impact

• Orgs are inadvertently cutting off AI-native talent from the workforce

• Misinformation, over-hype, and poor PR from big tech are fueling widespread public fear and distrust of AI

• AI adoption must move from top-down mandates to bottom-up innovation, empowering frontline workers

• Data quality is a foundational issue, especially in healthcare and other high-stakes domains

• Real opportunity is in leveraging AI to elevate human work through augmentation, creativity, and access

• Disconnection and over-reliance on AI are emerging as long-term social risks, especially for younger generations

Quotes

• “It’s a universal fear now. Everyone has to ask: what makes you AI-proof?”

• “The vitality of democracy depends on popular knowledge of complex questions.” 

• “We're not being given the option to say no to any of this.”

• “I’m 100% certain the current winners in AI will not be the winners in five to ten years.” 

Chapters

00:02 Welcome and Guest Introductions

00:48 MJ’s Path: From Computational Biology to Rural Healthcare

01:52 Why They Launched the Podcast You Teach the Machines

03:25 Jeff’s Work at CHOP and the Pediatric LLM Project

06:47 Making AI Understandable: The Book’s Purpose

09:11 Navigating Fear and Trust in AI Headlines

11:31 Gen Z, AI-Proof Careers, and Entry-Level Job Loss

16:33 Why Resilience is Gen Z’s Underrated Superpower

18:48 Disconnection, Dopamine, and the Social Cost of AI

22:42 AI’s PR Problem and the Survival Signals We're Ignoring

25:58 Chatbots as Addictive Companions: Where It Gets Dark

29:56 Choosing to Innovate: A More Hopeful AI Future

32:11 The Dirty Truth About Data Quality and Trust

36:20 How a Brooklyn Coffee Company Fine-Tuned AI with Their Own Data

40:12 Why “Throwing AI on It” Isn’t a Strategy

44:20 Measuring Productivity vs. Driving Meaningful Change

48:22 The Real ROI: Empowering People, Not Eliminating Them

53:26 Healthcare’s Lazy AI Priorities (and What We Should Do Instead)

57:12 How Gen Z Was Guided Toward Coding—And What Happens Now

59:37 Dependency, Education, and Democratizing Understanding

1:04:22 AI’s Impact on Educators, Students, and Assessment

1:07:03 The Real Threat Isn’t Just Job Loss—It’s Human Disconnection

1:10:01 Defaulting to AI: Why Saying "No" Is No Longer an Option

1:12:30 Final Thoughts and Where to Find Jeff and MJ’s Work

Jeff Pennington: https://www.linkedin.com/in/penningtonjeff/

Mary Jane Pennington: https://www.linkedin.com/in/maryjane-pennington-31710a175/

You Teach The Machines (book): https://www.audible.com/pd/You-Teach-the-Machines-Audiobook/B0G27833N9

You Teach The Machines (podcast): https://open.spotify.com/show/4t6TNeuYTaEL1WbfU5wsI0?si=bb2b1ec0b53d4e4e

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Enrique Rubio, Hacking HR, Transform, community building, democratizing learning, HR capabilities, AI governance, AI ethics, shadow AI, responsible AI, critical thinking, AI literacy, organizational risk, data privacy, HR community, learning access, talent development

Takeaways

• Hacking HR was founded to close capability gaps in HR and democratize access to world-class learning at affordable levels.

• The community’s growth accelerated during COVID when others paused events; Enrique filled the gap with accessible virtual learning.

• Many AI programs focus narrowly on prompting rather than teaching leaders to think, govern, and transform responsibly.

• Companies must assume employees and managers are already using AI and provide clear do’s and don’ts to mitigate risk.

• Untrained use of AI in hiring, promotions, and performance management poses serious liability and fairness concerns.

• Critical thinking is declining, and generative AI risks accelerating that trend unless individuals stay engaged in the reasoning process.

• Community must be built for the right reasons—transparency, purpose, and service—not just lead generation or monetization.

• AI strategies often overlook workforce readiness; literacy and governance are as important as tools and efficiency goals.

Quotes

• “Hacking HR is home for me.”

• “We’re here to democratize access to great learning and great community.”

• “Prompting is becoming an obsolete skill—leaders need to learn how to think in the age of AI.”

• “Assume everyone creating something on a computer is using AI in some capacity.”

• “If managers make decisions based on AI without training, that’s a massive liability.”

• “Most AI strategies can be summarized in one line: we’re using AI to be more efficient and productive.”

Chapters

00:00 Catching up and meeting in person at recent events

01:18 Enrique’s career journey and return to Hacking HR

04:43 Democratizing learning and supporting a global HR community

07:17 The early days of running virtual conferences alone

09:39 Why affordability and access are core to Hacking HR’s mission

13:13 The rise of AI programs and the noise in the market

15:58 Prompting vs. true strategic AI leadership

18:21 The importance of community intent and transparency

20:42 Training leaders to think, reskill, and govern in the age of AI

23:05 Dangers of data misuse, privacy gaps, and dark-web training sets

26:08 Critical thinking decline and AI’s impact on cognition

29:16 Trust, data provenance, and risks in recruiting use cases

31:48 The need for organizational AI manifestos

32:47 Managers using AI for people decisions without training

35:12 Why governance is essential for fairness and safety

39:12 The gap between stated AI strategies and people readiness

43:54 Accountability across the AI vendor chain

46:18 Who should lead AI inside organizations

49:28 Responsible innovation and redesigning work

53:06 Enrique’s personal AI tools and closing reflections

Enrique Rubio: https://www.linkedin.com/in/rubioenrique

Hacking HR: https://hackinghr.io

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Sandra Loughlin, EPAM, learning science, transformation, AI maturity, synthetic agents, digital twins, job displacement, data infrastructure, process redesign, AI literacy, enterprise AI, productivity, organizational change, responsible innovation, cognitive load, future of work

Takeaways

• Claims of massive AI-driven job loss overlook the real drivers: cost-cutting and reinvestment, not productivity gains.

• True AI value depends on re-engineering workflows, not automating isolated tasks.

• Synthetic experts and digital twins will reshape expertise, but context and judgment still require humans.

• Enterprise data bottlenecks—not technology—limit AI’s ability to scale.

• Humans need variability in cognitive load; eliminating all “mundane” work isn’t healthy or sustainable.

• AI natives—companies built around data from day one—pose real disruption threats to incumbents.

• Productivity gains may increase demand for work, not reduce it, echoing Jevons’ Paradox.

• AI literacy requires understanding technology, data, processes, and people—not just tools.

Quotes

• “Only about one percent of the layoffs have been a direct result of productivity from AI.”

• “If you automate steps three and six of a process, the work just backs up at four and seven.”

• “Synthetic agents trained on true expertise are what people should be imagining—not email-writing bots.”

• “AI can’t reflect my judgment on a highly complex situation with layered context.”

• “To succeed with AI, we have to lean into the thing that scares us.”

• “Humans can’t sustain eight hours of high-intensity cognitive work—our brains literally need the boring stuff.”

Chapters

00:00 Introduction and Sandra’s role at EPAM

01:39 Who EPAM serves and what their engineering teams deliver

03:40 Why companies misunderstand AI-driven job loss

07:28 Process bottlenecks and the real limits of automation

10:51 AI maturity in enterprises vs. AI natives

14:11 Why generic LLMs fail without specialized expertise

16:30 Synthetic agents and digital twins

18:30 What makes workplace AI truly dangerous—or transformative

23:20 Data challenges and the limits of enterprise context

26:30 Decision support vs. fully autonomous AI

31:48 How organizations should think about responsibility and design

34:21 AI natives and market disruption

36:28 Why humans must lean into AI despite discomfort

41:11 Human trust, cognition, and the need for low-intensity work

45:54 Responsible innovation and human-AI balance

50:27 Jevons’ Paradox and future work demand

54:25 Why HR disruption is coming—and why that can be good

58:15 The four pillars of AI literacy

01:02:05 Sandra’s favorite AI tools and closing thoughts

Sandra Loughlin: https://www.linkedin.com/in/sandraloughlin

EPAM: https://epam.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Keith Langbo, Kelaca, recruitment, hiring, talent acquisition, AI in recruiting, agentic systems, culture add, core values, psychometrics, responsible AI, fractional workforce, gig economy, recruiting automation, candidate experience, structured interviews, Kira, human-centric design, AI trust, global hiring, digital agents, recruitment tech, NLP sourcing, recruiting innovation

Takeaways

• Keith founded Kelaca to humanize the recruitment experience, treating people as partners — not products.

• Modern recruiting must shift from transactional, resume-driven models to more consultative, intelligence-based practices.

• AI’s greatest value lies in giving candidates and clients choice, not replacing humans — especially for real-time updates and communication preferences.

• Recruiters should move from “human-in-the-loop” to “humans in control” — using AI to augment but not automate judgment.

• Future hiring models may rely on digital agents representing both candidates and employers, enabling richer, data-driven matches.

• Core values — like kindness, accountability, and enthusiasm — are essential to maintaining culture across full-time and fractional teams.

• Structured data is key to overcoming bias and improving hiring quality, but psychometrics alone can't capture experience or growth.

• Many current tools automate broken processes; real innovation requires first rethinking what “better” hiring looks like.

Quotes

• “I wanted to treat people like people, not like products.”

• “AI powered but human driven — that’s the experience I want to create.”

• “Resumes are broken. Interviews are often charisma contests. We can do better.”

• “Humans don’t just need to be in the loop — they need to be in control.”

• “I don’t care if you’re full-time or fractional. You still need to show kindness and a willingness to learn.”

• “We’re on the verge of bots talking to bots. That’s exciting — and terrifying.”
  

Chapters

00:00 Introduction and Keith’s mission behind founding Kelaca

02:35 The candidate and client frustrations with traditional recruiting

05:10 Why resumes and interviews are broken — and what to do instead

07:10 Building feedback loops and AI-enabled candidate communication

10:45 Choice and context in AI tools: respecting human preference

13:44 From “human in the loop” to “human in control”

18:12 Agentic hiring and the rise of digital representation

25:10 Gig work and applying culture fit to fractional talent

29:34 Core values as the foundation of culture, not employment status

33:22 Responsible AI, fairness, and trust in hiring decisions

40:00 The hype cycle of recruiting tech and design thinking

42:56 AI as the modern calculator: from caution to capability

47:16 Global perspectives: AI adoption in US vs UK recruiting

53:08 Keith’s favorite AI tools and Kelaca’s new product, Kira

56:28 Closing thoughts and appreciation

Keith Langbo: https://www.linkedin.com/in/keithlangbo

Kelaca: https://kelaca.com/

KIRA Webinar Series: https://www.eventbrite.com/e/how-to-fix-the-first-step-in-hiring-to-drive-retention-introducing-kira-tickets-1853418256899

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords
Dan Riley, RADICL, Modern Survey, Aon, employee listening, people analytics, connection, trust, AI ethics, human-AI collaboration, imperfection, curiosity, creativity, collective intelligence, organizational network analysis, people analytics world, Unleash, Transform, learning culture, human connection, responsible AI

Takeaways

• Imperfection is a defining strength of humanity — and the source of creativity and innovation.

• The best technology solves real human problems in the flow of work, not just productivity gaps.

• AI is a mirror, amplifying human intent and behavior; if we lead with empathy and ethics, AI learns from that.

• Clarity, communication, and transparency are critical to avoiding “AI chaos” inside organizations.

• Continuous listening and connection are the new foundations for engagement and trust.

• Curiosity and conversation are essential skills for navigating the fast-moving future of work.

• The most effective teams balance diverse strengths rather than relying solely on “rock stars.”

• True progress happens when we keep the human conversation going — across roles, hierarchies, and perspectives.

Quotes

• “I define myself as an artist first — a musician, filmmaker, who randomly fell into HR and tech.”

• “The most beautiful part about being human is that we’re imperfect — that’s where the best ideas come from.”

• “AI doesn’t fix our flaws; it amplifies them. It’s a mirror of how we show up.”

• “For technology to work, it has to be solving a human problem in the flow, not just adding to the stack.”

• “It’s okay to say, ‘We don’t have it all figured out yet’ — just be transparent about where you are.”

• “You’ll never regret having a conversation about something important.”

Chapters

00:03 – Welcome and Dan’s background: from punk rock to HR tech

01:45 – Founding Modern Survey and RADICL’s mission around trust and impact

05:14 – The changing landscape of work

06:42 – Highlights from People Analytics World, Transform, and Unleash

09:50 – Rise of human connection as the dominant theme in work tech

13:10 – Clarity, communication, and the need for an AI strategy

16:19 – Productivity, balance, and reinvesting in people

18:36 – The risk of over-automation and the value of learning

22:16 – Teaching curiosity and critical thinking in an AI world

27:25 – Why open conversations about AI matter more than ever

33:51 – Employee listening, continuous dialogue, and the evolution of engagement

37:22 – How AI enhances understanding and connection between teams

40:06 – Organizational network analysis and adaptive learning

43:21 – Connection, mentorship, and collective intelligence

46:03 – AI as a mirror: amplification of human behavior and bias

48:36 – Building balanced, imperfect, and effective teams

51:48 – Tools, curiosity, and the limits of generative AI

55:35 – Trusting your judgment and maintaining critical thinking

56:34 – Staying human amid synthetic connection

57:45 – Closing reflections and the call for ongoing dialogue

Dan Riley: https://www.linkedin.com/in/dan-riley-57b9431

RADICL: http://www.radiclwork.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Brad Topliff, SelfActual, TIBCO, self-awareness, positive psychology, data ownership, digital identity, AI ethics, imagination, human-centric design, trust, internal mobility, talent data, distributed identity, psychological safety, future of work

Takeaways

• Self-awareness is foundational to effective teams and ethical AI use.

• Personal data about strengths and values should be owned by the individual, not the employer.

• AI can serve as a mirror and reframing tool, helping people build perspective—not replace human judgment.

• Internal mobility and growth depend on psychological safety and discretion around what employees share.

• Positive psychology and imagination can help teams align without reducing people to static personality types.

• The next era of HR tech should prioritize trust, transparency, and consent in how personal data is used.

• True human readiness for AI means combining durable human skills with thoughtful technology design.

Quotes

• “I became a translator between the arts, the engineers, and leadership—and that’s carried through everything I’ve done.”

• “When you create data about yourself, who owns it? You? Your organization? The answer matters for trust.”

• “Most people think they’re self-aware—but only about twelve percent actually are.”

• “A job interview is two people sitting across the table from each other lying. We both present what we think the other wants to hear.”

• “If you give people autonomy and psychological safety, they’ll show up more fully as themselves.”

• “In the presence of trust, you don’t need security.”

Chapters

00:03 – Welcome and Brad’s background in design, Apple roots, and TIBCO experience

05:46 – From UX to data: connecting human insight with enterprise technology

07:48 – Self-awareness, ownership of personal data, and building SelfActual

11:00 – The tension between authenticity, masking, and “bringing your whole self” to work

18:19 – Digital credentials, resumes, and rethinking candidate data ownership

23:08 – Internal mobility, verifiable credentials, and distributed identity

32:51 – Broad skills vs. specialization and the role of AI in talent matching

34:48 – Self-awareness, imagination, and positive psychology at work

46:48 – Rethinking internal mobility and autonomy for well-being and growth

49:26 – Human-centric AI readiness and the limits of automation

58:40 – Trust, security, and ownership of data in organizational AI systems

01:02:37 – Reflections on digital twins, imagination, and collective intelligence

01:08:06 – Closing thoughts and Self Actual’s human-first approach

Brad Topliff: https://www.linkedin.com/in/bradtopliff

SelfActual: https://selfactual.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords Humanly, conversational AI, AI interviewing, responsible AI, candidate experience, recruiting automation, employee engagement, AI acquisitions, ethics, RecFest, quality of hire, neurodiversity, candidate feedback, interview intelligence, AI coach, sourcing automation

Takeaways

• Humanly’s evolution includes three strategic acquisitions that expand its platform from candidate screening to post-hire engagement.

• The company’s mission is to help employers talk to 100% of their applicants—not just the 5% that typically make it through—and reduce time-to-hire.

• Prem highlights how AI can reduce ghosting by creating 24/7 availability and real-time Q&A touchpoints for candidates.

• Interview feedback tools and coaching features are being developed for both candidates and recruiters.

• The importance of AI workflow integration is critical—tools must operate within a recruiter’s day-to-day flow to be effective.

• Humanly’s platform helps uncover quality-of-hire insights by connecting interview behaviors with long-term employee outcomes.

• The need for third-party AI audits and ethical guardrails.

• Insights from diverse candidate populations—including neurodiverse candidates and early-career talent—are shaping Humanly’s inclusive design practices.

Quotes

• “It’s not human vs. AI—it’s AI vs. being ignored.”

• “Our goal is to reduce time-to-hire without compromising quality or fairness.”

• “We’re obsessed with the problem, not just the solution. That’s what keeps us grounded as we scale.”

• “Responsible AI should be audited just like SOC 2 or ISO—trust is foundational in hiring.”

• “The best interview for one role won’t be the same for another. That’s where personalization and learning matter.”

• “Everything we’ve done to improve access for neurodiverse candidates has made the experience better for everyone.”

Chapters

00:00 – Intro and Prem’s Background

01:00 – Humanly's Origins and the Candidate Experience Gap

03:00 – 2025 Growth, Funding, and Acquisition Strategy

05:15 – From Conversational AI to Full-Funnel Hiring Platform

06:30 – High-Volume and Knowledge Workers

08:00 – Combating Ghosting and Delays with AI Speed

10:30 – Candidate Support and Interview Feedback

12:00 – Creating a 24/7 Conversational Layer for Applicants

13:45 – Data-Driven Hiring and Candidate Self-Selection

15:00 – Interview Coaching and Practice Tools

17:00 – Acquisitions and Platform Consolidation Feedback

18:45 – Responsible AI and Third-Party Auditing

21:00 – Partnering with Values-Aligned Teams and Investors

22:00 – Measuring Candidate Experience Across All Interactions

24:00 – Connecting Interview Behavior to Quality of Hire

26:00 – Coaching Recruiters and Interview Intelligence

28:45 – Expanding Into Post-Hire and Internal Conversations

30:00 – The Future of AI in HR and Internal Use Cases

34:00 – Designing Inclusively for Diverse Candidate Needs

36:00 – Modalities, Accessibility, and Equity in Interviewing

39:00 – Generative AI Reflections and Everyday Use

42:00 – Wrapping Up: What's Next for Humanly

Prem Kumar: https://www.linkedin.com/in/premskumar

Humanly: https://humanly.io

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords AI in podcasting, HR tech, authenticity, podcast search optimization, personalization, digital identity, privacy, digital twins, agentic internet, audience engagement, AI tools, discoverability, content creation, automation, human connection

Takeaways

• Podcasting has evolved from a solo pursuit to a collaborative, AI-empowered craft.

• Optimization now means being discoverable by AI, not just by search engines.

• AI is already embedded throughout the creative workflow — from editing to marketing.

• Personal authenticity builds lasting trust in an algorithmic world.

• Digital twins and personalization raise questions about identity, privacy, and consent.

• Good content isn’t manipulation — it’s value shared with intention and empathy.

• True innovation comes from staying curious, playful, and human.

Quotes

• “We’ve moved from search to conversation — people don’t Google anymore, they ask.”

• “Independent podcasting can be lonely, but community turns it into a craft.”

• “You can’t automate authenticity, but AI can help you amplify it.”

• “If your content has value, you’re not gaming the system — you’re serving people.”

• “Privacy is an illusion. So, make the ads you see worth your time.”

• “Digital twins may not replace us, but they’ll definitely outlive us.”

Chapters

00:00 – Welcome and introduction

00:26 – William’s 25-year journey in HR tech and podcasting

02:47 – The evolution of Elevate Your AIQ and lessons from early episodes 05:25 – From SEO to PSO: Optimizing for AI discoverability

09:06 – Why AI-driven content isn’t manipulation when it adds real value

10:39 – Building community through the Work Defined Podcast Network

13:44 – Experimentation, creativity, and learning from other hosts

16:23 – How AI is transforming podcast production workflows

19:17 – Forgetting, hallucinations, and the limits of AI memory

21:48 – Digital twins and the blurred lines between personal and professional identity

26:32 – Authenticity online: the “one-dimensional self”

31:39 – Privacy illusions and the myth of online anonymity

33:57 – The “agentic internet” and the power of individual terms

38:25 – Advertising, personalization, and the importance of relevance

41:58 – Lazy marketing, weak signals, and bad outreach

46:46 – Aggregating knowledge and curating content intelligently

51:01 – Content creation, subscriptions, and the value of giving before selling

53:43 – AI, equity, and unlocking untapped talent

57:34 – Closing reflections and the case for empathy in technology

William Tincup: https://www.linkedin.com/in/tincup

WRKdefined: https://wrkdefined.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

AI hiring, structured hiring, recruiting technology, Greenhouse, Real Talent, Dream Job, hiring fairness, candidate experience, identity verification, deepfakes, AI doom loop, prompt injection, job seeker experience, future of work, skills-based hiring, authenticity in hiring, mission-driven leadership, HR tech

Takeaways

• AI can enhance hiring but must not replace human connection and judgment.

• The “AI doom loop” is eroding trust between employers and candidates.

• Real Talent helps companies identify legitimate, high-intent applicants.

• Dream Job empowers real people to rise above automated applications.

• Employers should be transparent about how AI is used in hiring decisions if they want to build trust while improving their employer brand.

• The résumé’s role is fading as new ways of showcasing skills emerge.

• The future of hiring belongs to organizations that unite data, empathy, and trust.

Quotes

• “Our mission is to help every company be great at hiring — and that means putting structure and fairness at the center.”

• “We’re caught in an AI doom loop where both sides are using automation to outsmart the other — and no one’s winning.”

• “You can’t automate authenticity. The human element is what stands out most in a world full of AI slop.”

• “We can do anything, but we can’t do everything. So we focus on what matters most: helping people connect in meaningful ways.”

• “It’s not about banning AI — it’s about setting clear expectations for how to use it responsibly.”

• “The death of the résumé has been predicted for decades, but maybe this is finally the time.”

Chapters

00:00 – Welcome and introduction

00:44 – Greenhouse origin story and mission

02:50 – Lessons from Dan’s early career and the importance of structured hiring

06:00 – Hiring for skills and potential over pedigree

08:20 – How structured interviews and scorecards create fairness and better data

11:00 – Balancing mission and business success at Greenhouse

13:40 – Introducing Real Talent and solving the “AI doom loop”

16:50 – Detecting fraud, misrepresentation, and risk in job applications

18:45 – Partnership with Clear for verified identities

20:00 – Digital credentialing and transparency in hiring

22:30 – The “AI vs. AI” challenge: automation on both sides of the hiring equation

25:00 – Dream Job: Human intent meets AI efficiency

27:50 – The candidate experience crisis and how to fix it

30:20 – Why resumes and job descriptions are losing meaning

32:00 – Bringing humanity back to hiring in an AI-dominated world

34:30 – The future of the HR tech ecosystem and partnerships

40:00 – Agentic AI and the next frontier of recruiting technology

43:00 – The death of the résumé and what replaces it

47:00 – Skills, AI literacy, and the next generation of workers

52:00 – Setting clear expectations for AI use in hiring

55:00 – Personal AI use: augmenting human connection

56:00 – Closing thoughts and reflections

Dan Chait: https://www.linkedin.com/in/dhchait

Greenhouse: https://greenhouse.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

UiPath, agentic AI, automation, digital workers, RPA, HR technology, AI governance, AI literacy, talent acquisition, responsible AI, workforce transformation, human-centric design, reskilling, change management, future of work, CHRO, culture shift, AI readiness

Takeaways

• UiPath’s transition from RPA to agentic automation marks a broader shift in how digital and human workers collaborate.

• HR has a central role in driving culture, trust, and adoption around emerging AI tools.

• A grassroots approach to agent development—crowdsourcing over 500 ideas from employees—ensures relevance and engagement.

• AI governance must evolve with technology; dedicated roles and frameworks are key to managing bias, access, and compliance.

• Building AI literacy across the organization—through tiered training and internal tooling—helps democratize innovation.

• Recruiting is transforming, but human relationships remain critical, especially in engaging passive candidates and senior-level talent.

• Not every task should be automated—some skills, like creative writing or candidate engagement, lose value when over-automated.

• Over-automation can create long-term talent gaps; junior roles are vital for succession and cultural continuity.
  

Quotes

• “It’s not just a technology-led transformation. Culture has to be a core part of the AI journey.”
• “Over 50% of my HR team are citizen developers—we’ve built that capability into our DNA.”
• “We crowdsourced more than 500 ideas for agents across the organization—and everyone had a voice.”
• “Just because you can automate something doesn’t mean you should. Human context still matters.”
• “AI literacy is about imagination as much as it is about instruction. People need to see what’s possible.”
• “I’d like to create a workplace where human connection still matters—even as agents take on more tasks.”
  

Chapters 00:00 – Introduction and Agi’s Career Path to UiPath

03:00 – From RPA to Agentic Automation

05:00 – HR at the Crossroads of Tech and Culture

07:15 – Org Design with Digital Coworkers

10:30 – Building Trust in Agentic Systems

13:40 – Responsible AI in HR Contexts

17:00 – Prioritizing and Tracking Agent Development

19:00 – Building AI Literacy Across the Organization

22:30 – From Vision to Execution: Pilots and Production

24:10 – Cross-functional Use Cases and Orchestration

26:45 – Governance, Compliance, and Continuous Oversight

30:00 – Redefining Human Skills in the Age of AI

33:00 – Knowing When Not to Automate

35:40 – Long-term Impacts on Junior Roles and Succession

38:45 – Strategic Workforce Planning and Digital Labor

41:00 – Agents in Recruiting: Limits and Opportunities

44:00 – Maintaining Human Relationships in Talent Acquisition 48:00 – Executive Search, Talent Advisors, and the Future of Recruiting

51:30 – Agi’s Personal Use and Reflections on GenAI

54:00 – Balancing Utility, Trust, and Critical Thinking

55:30 – Closing Thoughts and Wrap-up

Agi Garaba: https://www.linkedin.com/in/agnesgaraba

UiPath: https://uipath.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

AI in education, student agency, maker-centered learning, design thinking, STEAM, lifelong learning, workforce readiness, future of education, educational disruption, personalized learning, human skills, ethical AI, K-12 innovation

Takeaways

• AI is a disruptor that can serve as a catalyst for rethinking teaching and learning.

• Student agency—not content mastery—is the core skill for future-ready learners.

• Traditional education systems are misaligned with the skills needed for the future workforce.

• Hands-on, project-based learning nurtures creativity, empathy, and real-world problem solving.

• Educators must experiment, fail forward, and reimagine their roles.

• Community support is critical for educational transformation.

• Ethics, responsible use, and digital literacy must be part of AI education, and must start early.

• AI levels the playing field for diverse learners but must be designed and used thoughtfully.

Quotes

• “I never ask for permission. I just ask for forgiveness—and sometimes not even that.”

• “The big question is: what content is truly important for students to learn—and what can they master on their own?”

• “Agency is the kernel. If students have it, they can be resilient, adaptive, and self-directed.”

• “We want to create curious, empathetic humans who know they can change the world.”

• “AI doesn’t live a life—it can’t replace the embodied experience of being human.”

• “Schools need community conversations, not mandates, to adopt AI responsibly and equitably.”

Chapters

00:00 – Lisa Yokana’s background and the early signs of educational misalignment

02:35 – Leaving the classroom to consult globally on innovation and mindset

03:25 – Reframing education: Skills vs. content

06:20 – Nurturing student agency and tackling big problems

09:01 – The disconnect between education and workforce needs

12:56 – How Lisa gained support and built the Scarsdale Design Lab

17:29 – Parent engagement and community buy-in

20:59 – Integrating AI in meaningful, ethical ways

24:06 – Educator mindsets and reframing pedagogy around AI

27:26 – AI use starts younger than we think

29:24 – Rethinking college in the age of AI

35:33 – Global patterns in AI adoption across education systems

39:20 – Addressing neurodiverse needs and accessibility

42:24 – Broadening community engagement and “thinking out loud”

43:38 – Responsible AI use and responsible design

49:11 – Big Tech’s role and thoughtful AI adoption in schools

53:03 – Final advice for parents, educators, and students

Lisa Yokana: https://www.linkedin.com/in/lisa-yokana-81787ba

Next World Learning Lab: https://nextworldlearninglab.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Revelio Labs, Ben Zweig, labor market data, job architecture, workforce analytics, strategic workforce planning, AI in HR, cognitive computing, IBM, labor economics, generative AI, skills-based hiring, public labor statistics, contingent workforce, gig economy, talent intelligence

Takeaways

• Revelio Labs aims to recreate company-level workforce insights using publicly available employment data, similar to how Bloomberg transformed financial markets.

• Job architecture is built on three distinct but interrelated taxonomies: occupations, tasks, and skills.

• Many orgs think of skills as the building blocks of jobs, rather than attributes of people—a conceptual misstep that limits strategic planning.

• Gen AI is being used to score the automation vulnerability of tasks, enabling better insights into how work is changing.

• Strategic workforce planning is often misnamed—what most companies do is operational, not truly strategic.

• Contingent and freelance labor remains a blind spot in many traditional labor statistics and HR systems.

• The ability to adjust for data bias, reporting lags, and incomplete workforce signals is critical for creating trustworthy insights.

• Revelio’s Public Labor Statistics offers an independent source of macro labor data, complementing BLS and ADP methodologies.

Quotes

• “Skills are attributes of people. Tasks are the building blocks of jobs.”

• “What’s exciting is that these are hard problems with big upside—unlike finance, where most of the low-hanging fruit is gone.”

• “We’re asking LLMs to tell us what they’re good at—and how confident they are in that judgment.”

• “Most organizations don’t need to pay $1M to build a taxonomy anymore. They just need the right approach and the right data.”

• “There’s no reason we shouldn’t be repurposing labor market insights to help individuals, not just institutions.”

Chapters

00:00 — Intro and HR Tech reflections

02:08 — Ben’s background in economics and IBM analytics

06:43 — Why labor market data lags behind capital markets

09:22 — Building a flexible, bias-adjusted analytics stack

14:19 — Empathy for job seekers and candidate friction

16:10 — Why job discovery is fundamentally an information problem

19:53 — Unpacking job architecture: occupations, tasks, and skills

24:28 — Scoring AI’s impact on tasks, not skills

28:39 — Summarization vs. hallucination in generative AI

38:45 — Introducing RPLS: Revelio Public Labor Statistics

45:40 — The challenge of tracking freelance and contingent work

51:58 — Dealing with ghost data and workforce ambiguity

53:35 — Real-life uses of AI and Ben’s curiosity mindset

54:42 — Closing thoughts

Ben Zweig: https://www.linkedin.com/in/ben-zweig

Revelio Labs: https://reveliolabs.com

Job Architecture (pre-order): https://www.amazon.com/Job-Architecture-Building-Workforce-Intelligence/dp/1394369069/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

AI hiring, employment discrimination, bias audits, compliance, workplace fairness, age discrimination, Title VII, DEI backlash, Workday lawsuit, SiriusXM lawsuit, EU AI Act, risk mitigation, HR technology, candidate experience

Takeaways

• Employment discrimination laws apply at every stage of the talent lifecycle, from recruiting to termination.

• States like New York, Colorado, and California are setting the pace with new AI-focused compliance requirements.

• Employers face challenges managing a patchwork of state, federal, and international AI regulations.

• Recent lawsuits (Workday, SiriusXM) highlight risks of bias and disparate impact in AI-powered hiring.

• Candidate experience remains a critical yet often overlooked factor in mitigating both reputational and legal risk.

• Employers must balance the promise of AI with the responsibility to ensure fairness, accessibility, and transparency.

• Pay equity and transparency represent promising use cases where AI can drive positive change.
  

Quotes

• “Discrimination can happen at any stage of the employment process.”

• “Some state laws go as far as requiring employers to proactively audit their AI tools for bias.”

• “Employers can’t just outsource their hiring funnel and blindly take the recommendations of AI.”

• “Class actions often succeed where individual discrimination claims struggle — they reveal systemic patterns.”

• “Even if candidates don’t get the job, a little touch of humanity goes a long way in making them feel respected.”

• “AI has real potential to help employers get to the root causes of pay inequity and model solutions.”
  

Chapters

00:00 – Welcome and Introduction

00:36 – Emily’s background and role at Brightmine

02:38 – Overview of employment discrimination laws

05:27 – AI and compliance with existing legal frameworks

07:20 – California’s October regulations and employer liability

09:54 – Employer challenges with multi-state and global compliance

11:26 – Proactive vs reactive approaches to AI bias

13:06 – EU AI Act and global alignment strategies

15:37 – High-risk AI use cases in employment decisions

18:34 – DEI backlash and its impact on discrimination law

20:59 – Age discrimination and the Workday lawsuit

27:34 – Data, inference, and bias in AI hiring tools

31:25 – Candidate experience and black-box hiring systems

33:33 – Bias in interviews and the human role in hiring

37:43 – Transparency and feedback for candidates

42:44 – AI sourcing tools and recruiter responsibility

47:52 – Risks of misusing public AI tools in hiring

50:12 – The SiriusXM lawsuit and early legal developments

54:08 – Candidate engagement and communication gaps

59:19 – Emily’s views on AI tools and positive use cases

Emily Scace: https://www.linkedin.com/in/emily-scace

Brightmine: https://brightmine.com

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

Keywords

Responsible AI, Agentic AI, HR transformation, AI Playbook, AI readiness, AI literacy, reskilling, upskilling, internal mobility, ServiceNow, people analytics, AI enablement, human-centric, HR-IT collaboration, future of work, AI governance, workforce planning

Takeaways

• ServiceNow’s HR team is leading internal AI adoption while helping shape product development through real-world use and feedback.
  

• The AI Playbook for HR Leaders provides a practical framework that blends vision with tactical execution.
  

• Responsible AI isn’t just a compliance exercise—it's a continuous process requiring monitoring, iteration, and cross-functional governance.
  

• ServiceNow’s AI Control Tower centralizes use case tracking, governance status, adoption metrics, and value realization.
  

• The AI Heat Map approach helps identify which tasks are most ripe for AI augmentation and where reskilling efforts should focus.
  

• Strategic reskilling efforts, like transitioning HR operations roles into people partner roles, show how AI can enable—not replace—human potential.
  

• HR-IT collaboration is essential to enabling governance, product experimentation, and sustained transformation.
  

• Upcoming research from ServiceNow estimates 8 million U.S. roles will be transformed by agentic AI in the next five years.
  

Quotes

• “This is a human transformation, not just a tech transformation.”
  

• “Responsible AI isn’t finished at launch—it needs to be continuously monitored.”
  

• “We call it the AI Heat Map—breaking down roles into tasks to see where AI can really help.”
  

• “Strategic workforce planning needs to evolve into strategic work planning.”
  

• “If AI doubles productivity, it should also unlock opportunities—not eliminate people.”
  

• “We want employees to feel safe using AI and know we’re committed to reskilling, not replacing them.”
  
  

Chapters

00:00 – Intro and Brandon’s background

02:00 – Brandon’s unique role in HR and product feedback loops

03:20 – Internal vs. customer-led innovation

04:24 – AI solution inventory and governance

07:18 – AI readiness, literacy, and cultural change

10:00 – Role-based skill development

12:00 – Embedding Responsible AI across the enterprise

14:36 – Balancing innovation with ethical oversight

17:50 – HR and IT collaboration at ServiceNow

20:45 – Agentic AI and workforce planning

23:47 – Case study: reskilling HR ops into people partners

29:03 – Why internal talent is often overlooked

33:21 – The evolving value of analytics in the AI era

36:58 – Importance of data quality and governance

40:32 – How AI will transform every role and industry

46:03 – Banking and reinvesting AI-driven time savings

48:27 – How ServiceNow filters and prioritizes AI ideas

49:18 – Teaser: upcoming research on agentic AI’s impact

51:06 – Personal AI tools and what’s exciting (or scary)

54:04 – Final thoughts and call to action

Brandon Roberts: https://www.linkedin.com/in/brandon-roberts-50796ba

AI Playbook for HR Leaders: https://www.servicenow.com/content/dam/servicenow-assets/public/en-us/doc-type/resource-center/ebook/eb-hr-role-in-ai-transformation.pdf

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Keywords

people analytics, talent intelligence, workforce planning, organizational network analysis, Lightcast, HR tech, Gen AI, quality of hire, job analysis, data storytelling, ethical AI, talent metrics, innovation, influence and persuasion, data infrastructure, Directionally Correct podcast

Takeaways

• People analytics is only valuable when it influences decisions.

• Evolution of HR tech is moving from digitization to “value-first” intelligence.

• Effective storytelling with data is about persuasion and influence, not charts.

• Despite its maturity, organizational network analysis (ONA) remains underutilized.

• Most companies are underinvesting in data infrastructure, even as they chase AI initiatives.

• A flexible framework for measuring quality of hire is more useful than a rigid definition.

• Job analysis is having a renaissance as AI demands a deeper understanding of work.

• Ethics in people analytics isn't just about governance — it's about virtue and trust.
  

Quotes

• “People analytics that doesn't influence decision-making is just overhead.”

• “We’re still digitizing HR — we haven’t even started to optimize it.”

• “Smart people assume their conclusions are self-evident, but that’s not how decisions are made.”

• “We need storytelling with data, but what we really need is persuasion with data.”

• “AI’s biggest challenge in HR isn’t capability — it’s data infrastructure and context.”

• “There’s no one watching the watchmen — ethics starts with the person in the seat.”

• “The study of work isn’t sexy, but it’s suddenly essential again.”
  

Chapters

00:02 - Welcome and Intro to Cole Napper

00:55 - Cole’s Career Journey

03:29 - Patterns Across Industries and the Illusion of Uniqueness

06:51 - Community, Knowledge Sharing, and Power of Consortiums

08:57 - Why Smart People Still Struggle to Influence with Data

11:33 - From HR Tech to People Analytics: Digitization vs. Value Creation

13:51 - Data vs. Self-Interest: Why Decisions Get Blocked

15:49 - Untapped Potential of Org Network Analysis

18:54 - Use Cases: Building Teams, Referrals, and AI-Enhanced Sourcing

25:17 - Cole’s Book: Why Now, and What It’s About

28:13 - Shifting from Cost Center to Profit Center in People Analytics

32:22 - People Analytics Leading AI Adoption in HR

35:31 - Probabilistic Thinking, Determinism, and Predictive Pitfalls

36:55 - Measuring Quality of Hire: Frameworks vs. Definitions

40:41 - AI Assistants, Prescriptive Insights, and Reinforcement Learning

44:26 - Data Infrastructure as the Real AI Unlock

48:25 - Strategic Work Planning in an AI-Enabled World

52:25 - Who Will Watch the Watchmen? Ethics and Virtue in Analytics

55:28 - Predictions vs. Deductions and Parting Thoughts

Cole Napper: https://www.linkedin.com/in/colenapper

Directionally Correct: https://wrkdefined.com/podcast/directionally-correct

"People Analytics": https://www.colenapper.com/book

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Keywords

AI in recruiting, expert systems, generative AI, candidate experience, skills-based hiring, talent ethics, AI literacy, job applications, bias in hiring, strategic workforce planning, Jones Beach lifeguard, recruiting tech, AI governance, human-centered design, talent intelligence, responsible AI

Takeaways

• AI isn't new — it's just louder now: Steve recalls early experiences with AI-like systems in the 1980s and draws parallels to today’s hype and fear cycles.

• Recruiters need more curiosity, less fear: Avoiding AI won’t make it go away — recruiters must engage, experiment, and understand where AI fits.

• The real problem? Poor inputs: Most job descriptions and resumes are terrible — AI can’t solve for that without better human collaboration.

• Bias goes both ways: If employers can use AI to screen resumes, candidates can use it to write them — the key is transparency and integrity.

• Quality of hire starts with better intake: Steve emphasizes the importance of understanding real business problems, not just scanning for keywords.

• Candidate AI vs Employer AI: The current debate needs to move past gut reactions and toward practical, equitable frameworks.

• We need new roles and metrics: From TA ethicists to agentic governance leads, the future workforce demands new capabilities.

• Recruiting is about inclusion, not gatekeeping: Steve’s philosophy centers on humanizing the process and finding reasons to say “yes.”

Quotes

• “If you can't audit it, don't automate it.”

• “The real challenge is working to include someone rather than exclude them.”

• “We're seeing artificial stupidity — not artificial intelligence.”

• “Being afraid of the ocean because of sharks is like avoiding AI because of hallucinations. You’ve got to get in the water.”

• “You can fight this, or you can plan for it. That’s it.”

• “Most people don't write good resumes. Most recruiters don't write good job descriptions. AI's not going to save us from that.”

Chapters

• 00:00 – Opening & Reconnecting with Steve Levy

• 03:01 – Recruiting Before Computers & the Rise of Expert Systems

• 08:12 – What AI Is (and Isn’t): Fear, Hype & Progress

• 13:17 – Strategic TA in an Agentic Era

• 21:07 – AI Literacy, Education & Workforce Readiness

• 28:11 – Candidates Using AI vs. Employers Using AI

• 36:45 – Problems with Job Descriptions, Resumes & Gatekeeping

• 45:24 – Ethics, Transparency & Legal Implications in Hiring AI

• 54:10 – Talent Intelligence & Strategic Workforce Planning

• 1:05:33 – The SiriusXM Lawsuit & Candidate Frustration

• 1:15:57 – Lifeguard Lessons for the AI Age

• 1:20:12 – Final Thoughts on What Comes Next
  

Steve Levy: https://www.linkedin.com/in/levyrecruits

Steve’s Blog: https://recruitinginferno.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Keywords

AI-powered market monitoring, synthetic personas, talent acquisition, influencer marketing, social analytics, Claude, Perplexity, scenario planning, digital twins, quality of hire, Obsidian, strategic planning, generative AI, Delphi method, social capital

Takeaways

• Marshall’s Journey: Marshall has spent his career identifying experts and building tools to surface valuable insights from social data.

• Synthetic Personas in Action: Using tools like Claude to create synthetic expert panels that evaluate documents, surface perspectives, and even challenge his own thinking.

• AI-Augmented Talent Scenarios: AI to simulate team compositions, evaluate candidates’ social behaviors, and even model potential collaboration outcomes.

• Monitoring the Market with AI: Building systems that detect early signals in markets — including environmental policy — using a mix of RSS, generative AI, and good old-fashioned curiosity.

• Digital Twins and Ownership: Exploring who owns the knowledge embedded in a “digital twin” of an employee — and how organizations might leverage them responsibly.

• Strategic Planning Reimagined: Using AI to model outcomes based on actions and strategies offers new ways to engage in scenario planning — not just in workforce contexts, but in grantmaking and innovation networks.

• Counterargument Workflows: Marshall shares his custom-built browser tool that generates counterarguments to online content using ChatGPT, promoting critical thinking and cognitive diversity.
  

  Quotes

• “I try to eat my own dog food — or drink my own champagne — when it comes to market monitoring.”

• “There’s gold in that data. We just have to figure out how to mine it responsibly and effectively.”

• “Synthetic personas are fast, cheap, and good enough to get the conversation started.”

• “What’s the strategy, what’s the output — and what’s the outcome? That’s where AI can help us model the messy middle.”

• “You can’t just look at someone’s codebase or resume — you need context, behavior, and communication patterns.”

• “I built a ‘counterargument bookmarklet’ to challenge the assumptions in what I’m reading online.”
  Chapters

• 00:00 – Welcome & Reconnection: Marshall’s Background and Journey

• 03:12 – AI Systems for Market Monitoring and Early Signal Detection

• 10:58 – The Evolution of Social Analytics and Social Capital

• 16:39 – Talent Acquisition, AI, and the Value of Social Footprints

• 24:57 – Scenario Planning with Synthetic Personas

• 32:05 – Driving Innovation through Grant Monitoring and Project Pairing

• 40:41 – From Digital Twins to Ethical Implications of AI in the Workforce

• 50:15 – Counterargument Workflows and Critical Thinking with AI

• 58:21 – Closing Thoughts: Responsible AI, Community, and the Road Ahead

Marshall Kirkpatrick: https://www.linkedin.com/in/marshallkirkpatrick

Earth Catalyst: https://www.earthcatalyst.co/

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Keywords

AI literacy, human-centric design, responsible AI, automation, digital assistants, content generation, neuro-linguistic programming, human-AI collaboration, ethical AI, digital tools, Colette Mason, trusted AI

Takeaways

• AI ≠ Automation: Many tasks called "AI" are really just workflow automation. It's important to distinguish between the two.
  

• Human-Centered Design Matters: AI tools should reflect human needs, limitations, and behaviors, especially when used in sensitive areas like hiring.
  

• The Hype Is Real—and Misleading: Over-promising on AI capabilities can hurt trust and morale. Colette urges a more grounded, realistic view.
  

• Use AI Where It Helps, Not Where It Hurts: Delegate the boring stuff, but don’t let AI speak in your voice without oversight.
  

• Authenticity Still Wins: Whether it's writing, speaking, or building a personal brand, being transparent about AI involvement builds trust.
  

• Responsible Use Is Everyone’s Job: From solo entrepreneurs to large enterprises, we all have a role in building and using trustworthy AI.
  

• Design for Real People: Most users aren’t tech-savvy. Tools need to be intuitive, safe, and aware of different user needs—including neurodiversity.
  

Top Quotes

• “I model people’s brains because I’m a hypnotherapist—and that’s actually a superpower in tech.”
  

• “There’s a lot of AI that isn’t really AI. It’s just automation with lipstick.”
  

• “The system has to read the room—it can’t just say ‘you didn’t give me all the info, mate.’”
  

• “Regular people need AI that helps them make it to their kids’ school play—not impress YouTube bros.”
  

• “Don’t replace yourself with AI. Do less, but make it more you.”
  

• “We’re not in the early innings—we’re still in warmups when it comes to AI literacy.”
  

Chapters

• 00:00 – Intro and Colette's Background
  

• 02:00 – AI Hype vs. Reality: What’s Really Happening
  

• 06:00 – Automation ≠ AI: Breaking the Misconceptions
  

• 10:30 – Building Human-Centered Tools and Workflows
  

• 17:00 – Responsible AI and “Designing for Safety”
  

• 24:00 – Fairness in Hiring and Interviewing with AI
  

• 30:00 – The Quality of AI-Generated Content
  

• 38:00 – Being Transparent About AI Use
  

• 44:00 – Ethics, Reputation, and the Court of Public Opinion
  

• 50:00 – Global Perspectives on AI Regulation
  

• 54:30 – Favorite Tools and Real-World Applications
  

• 01:00:00 – The Future of Personality in AI Models
  

• 01:03:30 – Closing Thoughts
  

Colette Mason: https://www.linkedin.com/in/colettemason

Clever Clogs AI: https://www.cleverclogsai.com/

Ditch Rework, Build Teamwork: https://www.amazon.com/Ditch-Rework-Build-Teamwork-Principles-ebook/dp/B0FBL4C6ZP

For advisory work and marketing inquiries:

Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠

Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠

Substack: ⁠https://elevateyouraiq.substack.com⁠

What’s Your AIQ?⁠ Assessment interest form

Keywords

Enterprise Intelligence, Knowledge Management, Tacit Knowledge, Bloomfire, Enterprise AI, Digital Assistants, Leadership, Strategic Workforce Planning, Culture, Cognitive Diversity, Collective Intelligence, Human-Centricity, Trust, Future of Work, Ethical AI

Key Takeaways

Knowledge is an asset: Companies often fail to treat knowledge—especially tacit knowledge—as a formal asset on the balance sheet.

AI elevates knowledge management: The rise of AI has pushed KM into the C-suite, with a growing emphasis on enterprise-wide integration.

Tacit knowledge loss is costly: Orgs lose significant institutional knowledge without realizing its overall impact.

Trust drives knowledge sharing: Cultural factors, psychological safety, and leadership behavior directly impact how willing employees are to share knowledge.

Remote work challenges knowledge flow: For early-career professionals, the hybrid environment can inhibit mentorship and exposure to institutional wisdom.

Digital advisors & AI agents are rising: As digital personas and assistants become more advanced, organizations must consider the ethical implications.

SWP evolution: Strategic workforce planning should evolve into strategic work planning, balancing both digital and human contributions.

Measuring value requires new KPIs: Bloomfire’s framework ties knowledge value to tangible outcomes like revenue per employee, onboarding speed, and OKR attainment.

Cognitive diversity is crucial: Varied perspectives and experiences within teams lead to better problem-solving and innovation.

AI is integral to the future of work: It will require a blend of human and AI capabilities and should remain human-centric.

• “Tacit knowledge is going out the door, and companies are underestimating how consequential that is.”

• “AI systems are only as good as the quality of the knowledge you feed them. It’s still garbage in, garbage out.”

• “Organizations need to think of themselves as ecosystems, where people and digital agents work together.”
  

• “Cognitive diversity is going to be critical—otherwise everyone’s just prompting the same chatbot.”
  

Chapters

00:00 – Welcome and Guest Introduction

02:00 – Dan’s Career Journey and Road to Bloomfire

05:00 – What Bloomfire Does and the Rise of Enterprise Intelligence 08:30 – The Evolution of KM

12:00 – AI’s Role in Driving KM to the C-Suite

15:00 – Tacit Knowledge: The Hidden Asset

18:30 – The Value of Human-Centric Design in AI Strategy

24:00 – Skills Atrophy and the Impact of Remote Work

27:30 – Cognitive Diversity in the Age of AI

30:00 – Capturing Institutional Knowledge Through Tech

35:00 – Lessons from Early Expertise Discovery Tools

38:00 – Digital Advisors and the Risk of Redundancy

44:00 – Meeting Intelligence and Ethical Knowledge Capture

47:00 – Trust, Culture, and the Role of Leadership

55:00 – Experimentation, Risk, and AI Governance

59:00 – Innovation, Strategy, and the Future of Work

Dan Stradtman: https://www.linkedin.com/in/danstradtman

Bloomfire: https://bloomfire.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Keywords

Tekletics, AI, workforce development, talent acquisition, future of work, technology, coding bootcamp, human potential, automation, career transition

Takeaways

Tekletics aims to bridge the gap between untapped talent and technology careers.

The evolution of Tekletics reflects the changing landscape of work and technology.

Work ethic and a strong interest in technology are crucial for success in tech roles.

AI is transforming talent acquisition and development processes.

Organizations need to foster a culture of AI responsibility and ethical use.

The future of work will involve collaboration between humans and AI.

There are untapped talent pools that organizations can explore for hiring.

Training programs should focus on real projects rather than traditional boot camps.

AI tools can enhance productivity but must be used with caution.

Building a diverse and skilled workforce is essential for the future. 

Sound bites

"We need to tap into untapped human potential."

"We want to build a culture of AI responsibility."

"We have to help build the next generation of SMEs."

Chapters

00:00 Introduction to Tekletics and Casey Fox's Journey

03:23 The Evolution of Tekletics and Its Mission

08:46 Understanding the Future of Work and Career Pivots

16:02 Identifying Talent and Building Skills for the Future

20:00 Adapting to Changing Client Demands and AI Integration

25:09 Navigating the Talent Ecosystem and Future Opportunities

33:27 Navigating the Dystopian Path of AI

34:20 Fostering Curiosity in the Age of AI

36:22 The Evolution of Learning: Libraries vs. AI

38:32 Empowering Employees with AI: Trust vs. Control

40:33 The Human Element in AI Adoption

42:01 Building Trust in AI: Data Privacy Concerns

44:41 The Role of AI in Coding: A Double-Edged Sword

47:50 The Future of Junior Roles in a Tech-Driven World

51:17 Building a Foundation for Future Generations

55:28 AI Literacy: Understanding Risks and Opportunities

59:25 The Future of Work: Humans and AI Collaboration

01:02:55 Tekletics: Bridging the Gap for Future Talent

Casey Fox: https://www.linkedin.com/in/foxcase

Tekletics: https://www.tekletics.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

The conversation spans the origins of Metaview, the real cost of poor hiring decisions, and the gap between what hiring teams think they’re evaluating versus what they’re actually reacting to. They also discuss the difference between feedback and insight, the value of AI as an interview companion rather than a replacement, and why structured processes don’t have to come at the expense of candidate experience.

Keywords

Siadhal Magos, Metaview, interview intelligence, hiring decisions, quality of hire, feedback loops, AI in recruiting, structured interviews, candidate experience, decision-making, hiring bias, interview analytics, talent strategy, hiring intelligence, decision intelligence, summarization

Key Takeaways

Hiring is high-stakes—but under-instrumented. Most teams still rely on memory, gut feel, and incomplete notes.

AI can elevate—not replace—human judgment. Metaview focuses on supporting better decisions, not automating them away.
Interview feedback ≠ insight. Capturing what was said and how it was evaluated creates a far more useful learning loop.
Consistency doesn’t mean rigidity. Structured interviews can still be candidate-friendly and personalized.

Good hiring mirrors good product thinking. Siadhal shares how tight feedback loops, data, and clarity fuel both.

Curiosity is a superpower in early-stage building. The Metaview journey is a case study in iterating with empathy.

Top Quotes

“The way most interviews are run is far too fragile for the importance of the decisions being made.”

“We’re not trying to replace human judgment—we’re trying to give it better inputs.”

“Hiring is one of the most strategic things a company does, but it’s often the least measured.”

“It’s not just about the candidate’s answers—it’s about how the interviewer responded to them.”

“Great teams are built through consistent, reflective decision-making—not just instincts.”

Chapters

00:00 – Opening and Siadhal’s early career in product and people

06:45 – Why interviews are broken and how Metaview began

13:10 – Feedback vs. insight: a new lens on interview data

20:00 – The ethics and implications of recording interviews

26:35 – Human judgment + AI: striking the right balance

33:20 – Structured interviewing and candidate experience

40:50 – Building with curiosity: lessons from Metaview’s journey

47:00 – Final thoughts on quality of hire, trust, and team growth

Siadhal Magos: https://linkedin.com/in/siadhal

Metaview: https://metaview.ai

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Keywords

Kristi Broom, transformation, L&D, EdTech, generalist career, operational leadership, organizational change, innovation, behavior change, people development, systems thinking, storytelling in business, AI readiness, future of work

Key Takeaways

• Generalists are wired for transformation. Kristi explains how her generalist background allowed her to connect across silos and take on high-stakes change.

• EdTech roots shaped a systems mindset. Building early online learning systems taught her how to think structurally while staying flexible.

• Curiosity drives innovation. Kristi shares how being a “possibility thinker” has helped her evolve with each new challenge.

• Real transformation requires structure and story. Without storytelling, even well-designed systems fail to resonate.

• Growth is personal. Her work has always centered on helping people grow—whether through development programs, leadership models, or building intentional cultures.

• Pacing matters. When leading transformation, knowing when to accelerate—and when to pause—is a crucial leadership skill.

Top Quotes

• “I’ve always been a generalist—wired to think across disciplines, across people, across possibilities.”

• “Structure is important, but story is the engine that helps people move.”

• “I’m obsessed with seeing people grow. That’s where the energy comes from for me.”

• “You can't automate your way out of transformation—you still need leadership.”

• “My curiosity is a superpower, and I’ve learned how to use it to help people and organizations evolve.”

Chapters

00:00 – Opening and Kristi’s origin story in education and technology

08:15 – Becoming a generalist: curiosity, complexity, and change

14:30 – Early EdTech and learning platform design

20:45 – Making growth personal: L&D as a human imperative

27:10 – Leading transformation: structure, pacing, and storytelling

36:00 – Building future-ready systems without losing your people

42:55 – Final reflections on innovation, possibility, and what’s next

Kristi Broom: https://www.linkedin.com/in/kristibroom

Rising Tide Cooperative: https://risingtidecooperative.com

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Keywords

Andrew Gadomski, Aspen Analytics, workforce analytics, decision intelligence, data maturity, talent strategy, HR transformation, responsible AI, talent pipeline, future of work

Key Takeaways

• The difference between using AI as a prediction tool vs. a decision-making tool—and why that matters

• “Decision gravity” and how influence travels through an organization

• Why most organizations aren’t “data mature” and how to assess where you really are

• LLMs (like ChatGPT) aren’t ready to make decisions—they need guardrails, oversight, and smart humans

• The myth of a linear talent pipeline and how hiring should actually work

• Data-informed != data-driven: what smart decision-making really looks like

• How to frame AI adoption around people, not just tools

  
  

  Sound Bites

• “Data is a tool for influence—not control.”

• “If you don't trust the decision, you won't trust the data.”

• “AI will tell you what it would do. It won't tell you what you should do.”

  
  

  Chapters

• 00:00 – Welcome and Guest Intro Overview of Andrew’s role at Aspen Analytics and his approach to data-driven transformation.
  

• 05:10 – What “Data Maturity” Really Means Why most organizations overestimate their data capabilities—and what a mature approach actually involves.
  

• 12:40 – Decision Gravity and Influence Mapping How organizational decisions really get made and why influence—not hierarchy—is what drives outcomes.
  

• 21:25 – Prediction vs. Decision: The Role of AI Understanding how AI fits into human workflows, and why relying on LLMs for decisions is risky.
  

• 31:00 – The Limits of Large Language Models (LLMs) Where LLMs can be helpful, where they hallucinate, and how to set trust boundaries around their output.
  

• 40:30 – Hiring Myths and the Talent Pipeline Fallacy Why treating hiring like a “pipeline” misses the mark, and what a better model could look like.
  

• 52:15 – Building Trust Through Responsible AI How trust, transparency, and cultural readiness shape whether AI is embraced—or ignored.
  

• 63:00 – Reframing Success: Learning, Not Just Automation Closing reflections on how organizations can prioritize adaptability, curiosity, and practical value in the AI era.
  

• 72:30 – Final Takeaways and Where to Learn More Andrew’s parting thoughts on decision support, ethical data use, and leading with intentionality.

Andrew Gadomski: https://www.linkedin.com/in/andrewgadomski

Aspen Analytics: https://www.aspenanalytics.io/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Keywords

AI, HR technology, Oracle, automation, ethics, governance, education, community, human-centric, innovation, curiosity, creativity

Takeaways

• Chris Maurio has a background in HR and technology implementation.

• The HR tech space has evolved significantly over the past 20 years.

• Oracle is a leader in enterprise transformation and innovation.

• AI can enhance HR processes but requires careful governance.

• Human-centric design is crucial in AI applications.

• AI literacy should be part of onboarding and compliance training.

• Community plays a vital role in AI learning and collaboration.

• Education about AI should start early in schools.

• Curiosity drives innovation and effective use of AI.

• The future of work will involve a blend of human and machine capabilities.

Sound bites

"The innovation is incredible."

"Community is huge in this regard."

"Curiosity is key to learning AI."

Chapters

00:00 Introduction and Background

02:10 The Evolution of HR Technology

04:56 Oracle's Role in Enterprise Transformation

09:08 AI Integration in HR Systems

12:18 Governance and Compliance in AI

15:23 Human-Centric AI Design

19:19 AI Literacy and Training

22:19 Hands-On Learning with AI

27:28 The Future of AI Education

30:06 Closing Thoughts on AI and Education

30:45 Teaching Critical Thinking in the Age of AI

33:11 Integrating AI into Education

35:28 Balancing Screen Time and Learning

39:28 Fostering Curiosity and Critical Thinking

44:10 Navigating Trust and Ethics in AI

49:38 The Role of AI in Everyday Life

52:50 AI Literacy in Organizations

56:21 Community and Ethical AI Development

Chris Maurio: https://www.linkedin.com/in/chrismaurio

Argano: https://argano.com

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI coaching, Colleva, talent acquisition, employee insights, AI bias, sales coaching, healthcare training, performance management, responsible AI, technology summit

Takeaways

• Colleva started with AI coaching and has expanded its use cases.

• AI can play multiple roles in coaching and training.

• The platform is designed for high-performance environments.

• Colleva is being used in healthcare for role-playing scenarios.

• Sales coaching is a natural extension of their AI capabilities.

• AI can help standardize training and improve performance management.

• The platform allows for personalized and customized training experiences.

• AI bias is a critical concern that needs to be addressed.

• Colleva aims to empower employees rather than replace human interaction.

• The future of AI in recruitment is about providing fair opportunities. 

Sound bites

• "It's more situation specific."

• "We can practice and get it right."

• "Bias mitigation is critical in AI solutions."

Chapters

00:00 Introduction to Responsible AI and Colleva

02:14 The Genesis of Colleva and AI Coaching

04:49 Expanding Use Cases: From Coaching to Talent Co-Pilot

07:34 Target Markets: Financial Services and Healthcare

10:20 Sales Coaching: Enhancing Revenue Generation

13:04 Employee Insights and Performance Management

15:40 Customizing AI Interactions for Organizations

18:17 User Experience and Feedback on AI Avatars

22:45 From Marketing to Selling: The Evolution of Resumes

23:44 The Importance of 3D Candidate Presentation

25:26 Human-Centric Recruitment: Fairness and Respect

26:46 AI in Recruitment: Enhancing Human Interaction

30:13 AI Governance: Addressing Bias and Trust

34:16 Building Trust in AI Solutions

38:26 Creating a Unified Talent Experience

39:56 AI in Education: Tools for the Next Generation

45:25 Upcoming Events: The NYU Coaching and Technology Summit

Michael Palys: https://www.linkedin.com/in/mpalys/

Mike Patchen: https://www.linkedin.com/in/michael-patchen-39713214/

Colleva: https://www.colleva.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, recruitment, Braintrust, Adam Jackson, job market, technology, bias, user experience, talent acquisition, future of work

Takeaways

Adam Jackson has a rich entrepreneurial background in tech startups.

Braintrust is a tech jobs marketplace that uses AI to streamline recruitment.

Braintrust's AI Recruiter (AIR) solution is designed for fairness and scalability.

Candidates have reported feeling more relaxed during AI interviews.

AI can significantly reduce scheduling hassles in recruitment.

The job market is shifting towards AI-native skills.

AI can help sift through large volumes of applicants effectively.

Human oversight remains crucial in the recruitment process.

Organizations face skepticism when adopting AI technologies.

Continuous learning and adaptation are essential for future job seekers.

Sound Bites

"It's all about reducing friction."

"AI should and will do it."

"The skepticism is well deserved."

Chapters

00:00 Introduction to Adam Jackson and His Journey

02:28 The Evolution of Brain Trust and AI Integration

05:07 Addressing Bias in AI Recruiting

07:48 Candidate Comfort with AI in Recruitment

10:41 The Role of AI in Streamlining Recruitment Processes

13:27 Innovative Approaches to Candidate Assessment

16:19 Outbound Sourcing and Community Engagement

22:24 The Shift in Job Seeking Dynamics

24:58 Navigating the Evolving Job Market

28:20 Humans and AI: A Collaborative Future

30:47 Skepticism and Trust in AI Adoption

33:54 Assessing Candidate Skills with AI

37:58 Generative AI: Opportunities and Challenges

Adam Jackson: https://www.linkedin.com/in/ajackson

Braintrust: https://braintrust.com

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

improv, comedy, leadership, adaptability, workplace culture, AI, teamwork, human potential, leadership, AI integration, adaptability, education, creativity, change management, team success, human skills

Takeaways

• Joel Zeff transitioned from journalism to comedy and keynote speaking.

• Improv teaches valuable skills about adaptability and change.

• Fun in the workplace is essential for success and fulfillment.

• Creating a positive work culture involves supporting and empowering others.

• Joel's book encapsulates messages about leadership and teamwork.

• Change is inevitable, and how we react to it determines our success.

• Being prepared for change is crucial in any work environment.

• Fun means different things to different people.

• Embracing one's potential is key in the face of technological change.

• The journey of learning and adapting is ongoing and essential. Human potential is about taking control of one's path.

• Embracing change is crucial for success.

• Leaders should focus on helping their teams succeed.

• AI integration requires a balance between human and digital labor.

• Human skills are essential in the age of AI.

• Leadership is about building trust and relationships.

• Education must adapt to include AI literacy.

• Flexibility and adaptability are key in a changing world.

• Making mistakes is part of the learning process.

• Improv teaches us to be present and engaged.

Sound Bites

• "You choose to be prepared for change."

• "Stay in the game, find success."

• "How do I help my team be successful?"

• "AI should enhance human collaboration."

• "The future of work is human plus AI."

• "Education needs to incorporate AI."

• "Flexibility and adaptability are key."

• "Embrace mistakes to find freedom."

• "Control how we react to change."

Chapters

00:00 The Journey of Joel Zeff: From Journalism to Comedy

02:59 The Power of Improv: Embracing Change and Adaptability

05:50 The Importance of Fun in the Workplace

09:07 Creating a Positive Work Culture

12:11 Unpacking the Book: Messages of Leadership and Teamwork

14:54 Navigating Change in the Age of AI

18:06 Human Potential: Embracing Skills and Adaptability

26:25 Embracing Human Potential

27:17 Staying in the Game: Embracing Change

28:47 The Role of Leadership in Team Success

30:40 Navigating AI and Human Collaboration

33:10 The Importance of Human Skills in AI Integration

36:39 The Future of AI Leadership

40:30 AI in Creative Processes

43:37 Education and AI: A New Paradigm

45:31 Flexibility and Adaptability in a Changing World

49:05 The Freedom to Make Mistakes

Joel Zeff: https://www.joelzeff.com/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

What’s Your AIQ? Assessment interest form

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

AI, human-centric design, digital twin, personal intelligence, team dynamics, ethics, data ownership, future of work, meetings, AI literacy, personal intelligence, compensation structures, knowledge management, trust, transparency, ethical AI, human-centric AI

Summary

In this episode, Bob Pulver and Chris Heuer explore the intersection of artificial intelligence and humanity, discussing the implications of AI on teamwork, employment, and the future of work. They dive into concepts like digital twins and personal intelligence, emphasizing human-centric design and ethical considerations in AI integration. The conversation highlights the need for a shift in how we view collaboration and collective intelligence in the age of AI, while advocating for a more thoughtful approach to technology that prioritizes human values and relationships. Bob and Chris talk about AI literacy and readiness, and the implications for compensation structures in the workplace. They discuss ethical considerations surrounding AI design and use, and AI's influence on both career trajectories and organizational dynamics. 

Takeaways

• AI must be integrated with a focus on humanity.

• Understanding the long-term implications of AI is crucial.

• Digital twins represent personalized AI versions of ourselves.

• Terminology in AI shapes public perception and understanding.

• Ethical considerations are vital in AI development.

• Data ownership and privacy are essential in the AI landscape.

• Meetings should evolve into collaborative conversations.

• Calibrated trust in AI systems is necessary for effective use. 

• AI literacy encompasses ethical use and understanding privacy implications.

• Explaining AI's logic is crucial for trust and transparency.

• Sharing knowledge enhances personal and organizational growth.

• Compensation structures must adapt to recognize personal intelligence.

• Digital twins can optimize decision-making in teams.

• Curation of personal intelligence data is essential for quality.

• Licensing personal intelligence could reshape employment models.

• Trust is vital in navigating AI's impact on work.

• Organizations must prioritize human-centric approaches to AI.

Sound Bites

• "AI needs to start grounded in our humanity."

• "What does it mean for our roles in organizations?"

• "We need to consider human factors in AI integration."

• "AI can be a teammate, not just a tool."

• "We need to protect the value of human work."

• "Calibrated trust is essential with AI agents."

• "Sharing is power."

• "You could license me and charge $200 an hour."

• "Terminology has meaning, right?"

Chapters

00:00 Introduction to AI and Humanity

02:59 The Role of AI in Team Dynamics

06:01 Understanding Digital Twins and Personal Intelligence

08:54 The Implications of AI on Employment

12:10 Navigating Terminology in AI

14:58 The Future of Work and AI Integration

18:06 Personal Intelligence vs. Collective Intelligence

20:57 The Ethics of AI and Data Ownership

23:46 The Evolution of Meetings in the AI Era

27:02 Calibrated Trust in AI Systems

34:37 Understanding AI Literacy and Its Components

39:05 The Role of Personal Intelligence in Compensation

45:49 Navigating Knowledge Management and Digital Twins

50:04 Curating Personal Intelligence for Future Value

56:34 The Future of Work: Licensing Personal Intelligence

01:01:11 Trust and Transparency in the Age of AI

Chris Heuer: https://www.linkedin.com/in/chrisheuer

Team Flow Institute: https://teamflow.institute/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Substack: https://elevateyouraiq.substack.com

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Takeaways

• Education curriculum must evolve rapidly to keep pace with technological advancements.

• Personalized learning and coaching are essential for student success.

• Educational institutions need to focus on the purpose and outcomes of their programs.

• Technology can bridge gaps in education, especially for diverse learners.

• Critical thinking skills are crucial for navigating the complexities of the modern world.

• AI tools can enhance the coaching and mentorship experience.

• Flexibility in educational programs allows for personalized learning journeys.

• Integration of technology in education is inevitable and necessary.

• Future skills will require a blend of knowledge, adaptability, and critical thinking. Data access allows for continuous feedback in education.

• AI can transform performance management processes.

• Learning agility is essential in the modern workforce.

• Trust in AI coaching is growing among younger generations.

• Universities must adapt to the changing job landscape.

• Every job will become an augmented job with AI.

• Human connection remains vital in the workplace.

• AI can help individuals develop self-reflection skills.

• The role of middle management will evolve, not disappear.

• Continuous learning and adaptability are key to success.

Sound Bites

• "The educational model we've built is changing."

• "Education is not just about knowledge."

• "We need to create more flexibility for students."

• "We can provide feedback just in time based on data."

• "You need the ability to continuously learn."

• "Trust in AI coaching is higher than in human coaching."

• "Every job will be an augmented job."

• "We just need to be thinking about what's next."

Chapters

00:00 Introduction to Dr. Anna Tavis and Her Work

03:09 Evolution of Human Capital Management

06:05 Education in the Age of AI

09:03 Importance of Purpose in Education

11:53 Personalized Learning and Coaching

14:53 Role of Technology in Education

18:04 Future of Coaching and Mentorship

20:54 Bridging Gaps in Education with AI

24:04 Need for Change in Educational Practices

27:25 Power of Data in Education

30:33 Transforming Performance Management with AI

33:13 Learning Agility and the Role of AI

36:49 Trust in AI and Coaching

39:27 Role of Universities in a Changing Landscape

43:19 Redesigning Work in the Age of AI

Dr. Anna Tavis: https://www.linkedin.com/in/annatavis

NYU SPS: https://www.sps.nyu.edu/

NYU Coaching & Technology Summit: https://www.sps.nyu.edu/homepage/academics/divisions-and-departments/division-of-programs-in-business/human-capital-management/coaching-and-technology-summit.html

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Bianca Errigo, Human OS, wellbeing, performance, sustainability, mental health, coaching, technology, entrepreneurship, human-centricity, AI, organizational change, employee engagement, psychological safety, workplace culture

Summary

Bob Pulver speaks with Bianca Errigo, founder of Human OS, about her journey from tech sales to wellness expert and entrepreneur. Bianca shares her personal experiences with burnout and mental health, leading her to create Human OS, a platform that combines wellbeing, performance, and sustainability through personalized coaching and technology. The conversation explores the importance of support systems in maintaining high performance and how technology can enhance individual wellbeing. Bob and Bianca address organizational challenges with change, the impact of AI on workplace dynamics, and the importance of individual readiness and managerial support. The discussion emphasizes the need for open communication, co-creation, and a focus on human-centric values in the face of technological advancements.

Takeaways

• Bianca's career path is diverse and shaped by personal experiences.

• Burnout led Bianca to focus on mental and physical health.

• Human OS aims to make wellbeing accessible to everyone.

• The platform supports organizations in creating healthy work environments.

• Data tracking and habit tracking are key features of Human OS.

• Support and vulnerability are crucial for personal growth.

• Bianca has extensive coaching experience across various demographics.

• The intersection of technology and human expertise is vital for success.

• Sustainable high performance is achievable without compromising health.

• Entrepreneurship comes with its own set of challenges and rewards.

• Human OS combines wellbeing, performance, and sustainability.

• Most wellbeing solutions are reactive and not personalized.

• Organizations need to address cultural issues proactively.

• AI is often misunderstood and can create fear.

• Education about AI is crucial for both employers and employees.

• Change can be positive if managed correctly.

• Individual readiness impacts how change is received.

• Success is defined differently for each individual.

• Engagement and belonging are key to a fulfilled workforce.

• Co-creation with employees enhances AI adoption.

Sound Bites

• "AI can improve human experience and skills."

• "Communication is key during times of change."

• "We are all in this together with AI."

• "Organizations need to communicate openly about AI."

• "Involving employees as co-creators is crucial."

• "Don't bury your head in the sand about AI."

Chapters

00:00 Introduction to Bianca Errigo and Her Journey

03:04 The Evolution of Human OS and Its Mission

05:45 The Intersection of Wellbeing and Technology

10:00 Introduction to Human OS and Its Mission

12:11 Navigating Organizational Change and Culture

14:49 The Role of AI in Workplace Transformation

22:55 Individual Readiness and Managerial Impact

28:39 Embracing Change and Defining Success

35:28 Fostering Engagement and Co-Creation in AI Adoption

46:27 Preparing for the Future Workforce

Bianca Errigo: https://www.linkedin.com/in/biancaerrigo

HumanOS: https://humanos.co.uk/

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, recruitment, messaging, generative AI, ethics, job matching, candidate evaluation, transparency, testimonials, portfolios, digital profiles, AI recruitment, automation, candidate engagement, referrals, bias, curiosity

Takeaways

• GoHire started from a simple test to understand candidate communication preferences.

• The evolution from structured chatbots to generative AI is transforming recruitment.

• AI agents are becoming more autonomous and capable of assisting in HR tasks.

• Transparency in AI recruitment processes is crucial for ethical practices.

• Candidates are increasingly using AI tools to enhance their job applications.

• Public testimonials and portfolios are becoming essential in the hiring process.

• AI-driven job matching can create challenges for candidates.

• Authenticity in job seeking is more important than ever.

• The future of recruitment will rely on innovative assessment methods.

  Digital profiles are becoming essential for showcasing skills.

• Resumes are increasingly seen as outdated marketing documents.

• AI can enhance recruitment by analyzing candidate interactions.

• Engagement strategies can filter out less interested candidates.

• Referrals significantly increase the chances of getting hired.

• Bias exists in both human and algorithmic decision-making.

• Curiosity about AI can lead to innovative solutions.

• AI tools should be used thoughtfully and critically.

Sound Bites

"People are using messaging more and more."

"The resume's dead."

"AI tools will change recruitment."

"The hiring process is broken."

"You need to engage candidates."

"Bias exists throughout the system."

"You need to understand your unknowns."

"Curiosity drives innovation."

"You can't outsource critical thinking."

"Start using AI as a playground."

Chapters

00:00 Introduction to GoHire and Jonathan's Journey

03:06 The Evolution of Messaging in Recruitment

06:11 Generative AI and Its Impact on Recruitment

09:02 The Future of AI Agents in HR

12:09 Transparency and Ethics in AI Recruitment

15:05 AI in Candidate Evaluation and Job Matching

18:00 The Role of Public Testimonials and Portfolios

21:10 Navigating AI-Driven Job Applications

24:01 The Importance of Authenticity in Job Seeking

33:04 The Evolution of Digital Profiles

37:55 The Resume's Relevance in the AI Era

40:40 Automation in Recruitment Processes

46:00 Enhancing Candidate Engagement

47:48 The Power of Referrals in Hiring

53:54 Addressing Bias in Recruitment

59:46 Curiosity and AI: A Path to Innovation

Jonathan Duarte: https://www.linkedin.com/in/bestlinkedinprofile

GoHire: https://gohire.com

For advisory work and marketing inquiries:

Bob Pulver:⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠

Elevate Your AIQ:⁠ ⁠https://elevateyouraiq.com⁠⁠

Thanks to Warden AI (⁠⁠https://warden-ai.com⁠⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

HR technology, analytics, engagement, talent acquisition, internal mobility, workforce planning, employee journey, benchmarking, organizational agility, AI adoption, employee experience, human centricity, fairness, DEI, responsible AI, future workforce, automation

Takeaways

• The role of HR is being redefined, requiring more strategic insights.

• Companies are increasingly prioritizing data analytics in HR.

• Benchmarking helps organizations understand their performance relative to peers.

• Talent acquisition needs to align with internal mobility opportunities.

• AI is impacting 40% of jobs, changing roles in real-time.

• Connecting employee journeys is crucial for organizational success.

• Many companies lack the tools to effectively analyze their data.

• Organizations must adapt to leverage AI in their workforce.

• Dynamic organizations require agility in talent management. 

• Organizations often react to external factors instead of using available data.

• Human centricity must be prioritized in AI implementation.

• Fairness in AI should be integrated into every role, not just a department.

• Evaluating AI solutions requires a human-centric lens.

• Responsible AI education is essential for HR and talent acquisition.

• Critical thinking is necessary when using AI tools.

• The future workforce needs to be educated on AI literacy.

• HR leaders can automate time-intensive tasks to focus on strategic initiatives.

Sound Bites

• "Companies are prioritizing data more than ever."

• "Benchmarking gives them the reality check."

• "40% of jobs are going to be impacted based on AI."

• "It's instinct versus data and reality."

• "Are we making fair decisions about people's lives?"

• "This has to be a part of every single person's job."

Chapters

00:00 Introduction to Illoominus and Noelle's Background

03:06 The Evolution of HR and Data Analytics

05:46 Benchmarking and Talent Intelligence

08:50 Connecting Employee Journeys and Internal Mobility

11:52 The Role of AI in HR and Talent Acquisition

15:05 Challenges in Data Integration and Employee Engagement

17:48 The Future of Work and Organizational Agility

29:43 AI Adoption in Retail and Employee Data

34:26 Human Centricity in AI Implementation

36:54 Integrating Fairness in AI and DEI Initiatives

40:54 Evaluating AI Solutions with a Human Lens

44:45 Responsible AI and Critical Thinking

48:05 Preparing for the Future Workforce

49:46 Opportunities for HR Leaders in AI Adoption

Noelle London: ⁠https://www.linkedin.com/in/noellelondon⁠

Illoominus: ⁠https://www.illoominus.com/⁠

For advisory work and marketing inquiries:

Bob Pulver: ⁠https://linkedin.com/in/bobpulver⁠

Elevate Your AIQ: ⁠https://elevateyouraiq.com⁠

Thanks to Warden AI (⁠https://warden-ai.com⁠) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords: AI culture, human-AI collaboration, AI literacy, creativity with AI, education innovation, AI governance, co-intelligence, emotional intelligence, adaptability, future of work, book writing with AI, AI in K-12, AI in higher education, chief AI officer

Key Takeaways:

• AI collaboration should emphasize humanity, not just efficiency.

• Writing AI Culture Shift was a human-AI co-creation born of structure, trust, and transparency.

• EQ and AQ are just as important as IQ in the AI age.

• AI literacy must go beyond prompt engineering—ethics, critical thinking, and discernment are essential.

• Education needs to move from one-size-fits-all to personalized, thrive-based learning models.

• AI governance and training should be as foundational as cybersecurity protocols in today’s organizations.

• Building apps, writing books, and experimenting with AI can be accessible—even for kids—when curiosity is cultivated.

• The Chief AI Officer role is vital for navigating strategy, operations, and human impact across the enterprise.
  

Top Quotes:

• “This book is really about humanity more than it is about AI.”

• “AI hallucinates. Humans lie. You still have to verify.”

• “The creative process is personal—AI is just a powerful partner in that process.”

• “We didn’t just write a book with AI. We designed a new way of collaborating.”

• “AI literacy is not about prompting better—it’s about thinking better.”

• “The organizations that play with intention will thrive.”

Chapters:

Adnan Iftekhar: https://www.linkedin.com/in/aiineducation

Brian Moynihan: https://www.linkedin.com/in/brianmoynihan

“AI Culture Shift”: https://www.amazon.com/dp/B0DRDMVDFV

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

software consulting, AI, user experience, digital transformation, content supply chain, synthetic personas, product development, technology, AI, survey design, communication, responsible AI, software development, client readiness, education, workforce, digital transformation, human-centric AI

Takeaways

• Brian's journey from music to software highlights the importance of following one's passion.
• FM is a software consultancy that leverages AI to enhance business processes.
• AI is revolutionizing how software is developed and deployed.
• Custom software solutions can optimize business operations uniquely.
• The concept of 'human in the loop' is crucial in AI applications.
• Synthetic personas can enhance user testing and product development.
• Agile methodologies are essential for rapid product development.
• AI can transform entire processes, not just digitize them.
• FM aims to build as quickly as possible to gain insights and pivot effectively.
• AI can enhance corporate communication and training.
• Responsible AI emphasizes human oversight and understanding.
• The hype around AI is subsiding, leading to more realistic applications.
• AI is a tool that requires proper guidance and understanding.
• Client readiness for AI adoption varies significantly.
• Production challenges in AI implementation are substantial.
• Education must adapt to prepare future workers for AI.
• Critical thinking remains essential despite AI advancements.
• AI's role in society will continue to evolve and adapt.

Sound Bites

• "The entire process changes with AI."
• "You've sort of hyper accelerated that."
• "Humans should be in charge."
• "The hype cycle is dying down."
• "POCs are easy, production is hard."

Chapters

00:00 Brian Fletcher's Journey: From Music to Software

13:01 The Birth of FM: A New Era in Software Consulting

23:57 AI in Action: Revolutionizing Processes and Product Development

30:34 Survey Design and Data Collection Challenges

32:00 Applications of AI in Corporate Communication

32:46 Responsible AI and Human-Centric Approaches

34:50 The Hype Cycle of AI and Its Realities

36:35 Leveraging AI in Software Development

39:43 Understanding Client Readiness for AI Adoption

42:58 Challenges in Production and Adoption of AI Solutions

45:47 Education and Future Workforce Preparedness

Brian Fletcher: https://www.linkedin.com/in/brianfletcher

FM: https://buildfm.com

For advisory work, marketing inquiries and more AIQ content:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Substack: https://elevateyouraiq.substack.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy.

Keywords

AI, fairness, workplace equality, technology regulation, data-driven solutions, human-centric AI, accountability, hiring practices, diversity, inclusion, fairness, organizational performance, human-centric AI, pay gaps, work redesign, AI literacy, future of work, flexibility, diversity

Takeaways

• Importance of focusing on human-centric solutions amidst AI advancements.
• Growing need for a solution-centered approach to workplace equality.
• Testing and experimentation are critical in evaluating fairness solutions in the workplace.
• Analogy of clinical trials is used to stress the importance of rigorous testing for technology.
• Lack of regulatory oversight in technology similar to the FDA in medicine.
• Educated buyers can influence tech providers to be more transparent and accountable.
• Public accountability measures can drive companies to improve fairness and DEI efforts.
• Current uncertain climate in corporate America is one of caution and risk aversion.
• Everyday actions can lead to significant changes in fairness and inclusion, which is essential for organizational performance.
• Human-centric AI can enhance team effectiveness.
• Cognitive diversity is crucial for recognizing different use cases.
• AI prompts important conversations about skills and pay.
• Job roles should be redesigned to leverage human and AI strengths.
• AI literacy is vital for all workers, not just knowledge workers.
• Engaging with AI must be a core competency for all.
• Trust in AI outputs is necessary for effective use.

Sound Bites

• "We still focus on what makes us human."
• "We can do better than this in terms of fairness."
• "The future of work is humans plus AI."
• "We need cognitive diversity within teams."
• "AI literacy is critical across all industries."
• "No one should be left behind in AI training."
• "Engaging with AI is a core competency."
• "Trust is a huge factor in AI literacy."

Chapters

00:00 Introduction to Human-Centric Solutions

03:06 Exploring Fairness at Work

05:46 The Importance of Testing and Regulation

09:00 Data Maturity and Technology Challenges

12:05 Accountability in Technology Solutions

15:11 The Role of Buyers in Shaping Technology

18:09 Current Trends in Corporate America

21:13 The Future of Fairness and Inclusion

25:47 The Role of Fairness in Organizational Performance

27:11 Human-Centric AI: Enhancing Team Effectiveness

30:11 Addressing Pay Gaps and Job Valuation

33:03 Work Redesign: Human and AI Collaboration

36:43 Flexibility in Work Structures

38:25 The Importance of AI Literacy

45:55 Preparing Future Generations for AI Engagement

Siri Chilazi: https://www.linkedin.com/in/sirichilazi

“Make Work Fair”: https://makeworkfair.com/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

Deepgram, AI, voice technology, recruitment, machine learning, audio processing, talent acquisition, voice agents, PyTorch, company culture, human oversight, curiosity, global AI landscape, research and development, technology

Takeaways

• Deepgram is a voice AI platform that powers myriad applications.
• Scott transitioned from a career in particle physics to AI.
• The founding of Deepgram was inspired by the need for audio processing technology.
• AI can significantly enhance the recruitment process by automating initial conversations.
• Voice agents can provide a seamless customer experience in various settings.
• The accuracy and speed of AI models are crucial for their effectiveness.
• AI can help companies scale their recruitment efforts efficiently.
• Transparency in AI interactions is important for user acceptance.
• The future of AI in hiring will involve more personalized and interactive experiences. 
• Deep conversations reveal true understanding and capability.
• Human oversight is crucial in AI governance.
• Company culture should prioritize curiosity and learning.
• Deepgram's mission is to increase global productivity through audio.
• Voice communication is set to grow significantly in the coming years.
• The global AI landscape is competitive, with varying approaches in different regions.
• Investing in basic research is essential for future innovation.
• The best ideas should come from anywhere within the organization.
• Everyone in a company should think like a manager in the AI era.

Sound Bites

• "The best ideas win."
• "Curiosity is the top sign for Deepgram."
• "Deepgram is an intelligence company."
• "We're a learning company."
• "Communication is going to be key."
• "This is the intelligence revolution."
• "We need to invest in basic research."

Chapters

00:00 Introduction to Deepgram AI and Scott's Background

05:52 Transition from Physics to AI and Deepgram's Founding

12:01 Deepgram's Technology and Applications in Voice AI

17:58 AI in Recruitment: Transforming Talent Acquisition

24:00 The Future of AI in Conversations and Hiring Processes

26:02 Understanding PyTorch Expertise

28:10 The Importance of Human Oversight in AI

29:01 Company Culture and Human-Centric Approaches

30:19 Curiosity as a Core Value at Deepgram

32:14 Deepgram's Mission and Organizational Structure

34:55 The Future of Voice Communication

37:28 The Evolution of Communication Methods

39:46 The Global AI Landscape and Competition

52:24 Investing in AI Research and Development

Scott Stephenson: https://www.linkedin.com/in/scott-stephenson-

Deepgram: https://deepgram.com/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI literacy, AI maturity index, future of work, automation, augmentation, productivity, change management, digital transformation, workforce development, AI strategy, AI adoption, organizational maturity, competitive benchmarking, AI skills, hiring trends, cultural shifts, responsible innovation, AI governance, global AI perspectives

Takeaways

• AI literacy is crucial for the future of work.
• The AI maturity index helps organizations benchmark their AI readiness.
• The STEP framework simplifies AI implementation processes.
• Many organizations struggle with AI implementation despite having strategies.
• AI can enhance productivity and work-life balance.
• Understanding the real value of AI goes beyond cost savings.
• Personalized approaches to AI implementation are essential.
• The landscape of AI is rapidly evolving, requiring continuous learning.
• Measuring AI adoption success requires real data, not just anecdotes.
• Departments within organizations may have varying maturity levels in AI adoption.
• AI skills are becoming essential in hiring practices across industries.
• Cultural shifts are influencing how organizations embrace AI technology.
• Responsible innovation is crucial for leveraging AI effectively.
• AI governance must balance control with worker empowerment.
• Global perspectives on AI adoption reveal significant regional differences.
• Organizations need to adapt to the rapid pace of AI advancements.

Sound Bites

• "AI is going to steal your job."
• "We help individuals, teams and organizations."
• "Democratize access to insights."
• "80% of AI implementation projects are failing."
• "AI can really help fix a lot of challenges."
• "It's about making my life easier."
• "We need to start looking at real value."
• "This is what I'm doing right now."
• "We can go more in depth, more personalized."
• "We're all tech enabled in different ways."
• "This is a balancing act of guided empowerment."

Chapters

00:00 Introduction to AI Literacy and Maturity Index

03:49 Understanding the AI Maturity Index

11:44 The STEP Framework for AI Implementation

18:43 Navigating Automation vs. Augmentation

23:23 Measuring AI Value Beyond Cost Savings

25:55 Measuring Success in AI Adoption

30:23 Understanding Organizational Maturity in AI

31:21 The Competitive Edge of AI Benchmarking

32:58 The Future of AI Skills in Hiring

37:12 Cultural Shifts in AI Adoption

40:37 Responsible Innovation in AI

46:05 Navigating AI Governance and Ethics

50:00 Global Perspectives on AI Implementation

Eryn Peters: https://www.linkedin.com/in/erynpeters

Iwo Szapar: https://www.linkedin.com/in/iwoszapar

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

Clara, talent acquisition, human-centric AI, critical thinking, distance traveled, hiring strategies, AI ethics, neurodiversity, career development, AI, recruitment, hiring, transparency, ethics, equity, technology, job assessments, AI literacy

Takeaways

• Natasha's diverse background shaped her perspective on opportunities.
• Clara aims to help people tell their own stories better in job applications.
• The traditional resume often fails to reflect true capabilities.
• AI can enhance the talent acquisition process by providing real-time feedback.
• Critical thinking and learning agility are essential skills for the future workforce.
• Distance traveled measures potential relative to one's starting point.
• Hiring for potential can lead to more dynamic teams.
• Technology should enhance human interaction, not replace it.
• Neurodiversity should be considered in the hiring process.
• AI can enhance the recruitment process by providing better candidate insights.
• Transparency in AI usage is crucial for building trust with candidates.
• Companies must ensure ethical practices when using AI in hiring.
• AI literacy is essential for effective and responsible use of technology.
• Real-time assessments can help gauge a candidate's true capabilities.
• The future of work will involve collaboration between humans and AI.
• AI has the potential to address systemic inequalities in hiring.

Sound Bites

• "We are so much more than the job titles we've had."
• "How can we help people tell their own stories better?"
• "We need to hold on to the things that humans do best."
• "I'm bullish on AI conducting that interview."
• "There's nowhere to go but up from the current situation."
• "Great tools in the hands of great people do great things."
• "We have an opportunity to begin to level the playing field."
• "Garbage in, garbage out is always true."

Chapters

00:00 Natasha's Journey to Clara

05:11 The Mission of Clara

10:05 Innovative Talent Acquisition Strategies

14:56 The Importance of Critical Thinking

20:15 Navigating AI in Human Interaction

27:33 The Role of AI in Recruitment

30:28 Transparency and Ethics in AI Hiring

34:45 AI Literacy and Responsible Use

39:21 Real-Time Assessments and Job Relevance

43:01 Equity and Access in AI Technology

51:33 The Future of AI and Human Collaboration

Natasha Nuytten: https://www.linkedin.com/in/natasha-nuytten

Clara: https://getclara.io

Human Side Up: https://www.humansideup.com/insights-from-a-digital-transformation-pioneer/

Can AI Make Hiring More Human?: https://www.getclara.io/resources/ai-deib-can-artificial-intelligence-make-hiring-more-human

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Substack: https://elevateyouraiq.substack.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

leadership, AI, labor market, technology, creativity, job transformation, human skills, automation, storytelling, future of work, AI, creative writing, leadership, authenticity, thought partner, organizational success, technology, innovation, productivity

Takeaways

• AI is transforming leadership and productivity.
• The labor market is facing a shortage of workers.
• Technology can replace mundane tasks, freeing humans for higher-value work.
• Leadership must adapt to the changing landscape of work.
• Human creativity cannot be replaced by AI.
• AI can assist in generating ideas and scenarios for training.
• The importance of storytelling in leadership and creativity.
• AI's impact on job roles and responsibilities is significant.
• Leaders need to understand technology literacy.
• The future of work will require a balance between technology and human skills. 
• AI can generate initial drafts to overcome creative blocks.
• Many AI-generated ideas may be subpar, but some can be valuable.
• AI can help identify connections between disparate ideas.
• Leaders need to invest in their development for better organizational outcomes.
• Authentic relationships are crucial for effective leadership.
• AI can assist in practicing difficult conversations for leaders.
• Using AI can free up time for leaders to connect with their teams.
• AI can help summarize and filter relevant research papers.
• Organizations benefit from leaders who are approachable and engaged.
• AI can enhance the efficiency of content creation and repurposing.

Sound Bites

• "AI makes the jobs easier."
• "AI can't replace human creativity."
• "The creative process is uniquely human."
• "AI can help find connections."
• "The potential is just unlimited."
• "AI as a thought partner."
• "Authenticity is key in leadership."
• "There's a lot of promise for leaders."



Chapters

00:00 Introduction to Leadership and AI

03:04 The Impact of AI on Leadership

05:59 Navigating the Labor Market Changes

09:00 The Role of Technology in Job Transformation

12:02 Human Creativity vs. AI

15:09 The Creative Process and AI's Role

17:58 Refining Ideas with AI

28:16 Harnessing AI for Creative Writing

30:30 Augmenting Human Thought with AI

32:26 Finding Connections in Data

36:33 The Role of AI in Leadership Development

40:52 AI as a Thought Partner

43:29 Authenticity in Leadership

51:53 Investing in Leadership for Organizational Success

Phil Wilson: https://www.linkedin.com/in/pbwilson

LRI Consulting: http://lrionline.com

Leader Shift Playbook: https://yourleadershift.com

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Substack: https://elevateyouraiq.substack.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI adoption, employee experience, organizational policy, productivity, workforce dynamics, AI literacy, shadow AI, governance, communication, collaboration, superworker, mindset, storytelling, collective intelligence, team dynamics, innovation

Takeaways

• AI adoption is not matching the hype; many organizations lag behind.
• Employees feel disconnected from AI's potential benefits.
• Policy paralysis is stalling AI adoption in large organizations.
• A significant percentage of employees lack clarity on AI usage.
• Shadow AI poses risks to organizations and employee data security.
• There's a divide in the workforce between AI adopters and non-adopters.
• Team effectiveness is crucial for overall productivity.
• Communication about AI's value is essential for adoption.
• AI literacy is necessary for employees to leverage technology effectively. 
• Executives can influence brand reputation through transparency.
• Digital natives can mentor traditional executives on new technologies.
• Insular work cultures hinder innovation and productivity.
• Personal productivity improvements are not enough for transformation.
• The superworker concept emphasizes human-AI collaboration.
• Mindset shifts are necessary for effective AI integration.
• Storytelling is crucial for communicating AI's value.
• Collective intelligence can enhance team dynamics and innovation.

Sound Bites

• "The reality isn't matching up to the hype."
• "There's been a bit of a false start."
• "We need clarity and guidance for AI usage."
• "There's a schism in the workforce regarding AI usage."
• "How do I be the best version of myself?"
• "It's about the skill level and the actual competency."

Chapters

00:00 Introduction to AI Adoption and Employee Experience

03:08 The AI Adoption Gap: Reality vs. Hype

06:13 Understanding Employee Perspectives on AI

09:01 Policy Paralysis and Its Impact on AI Adoption

11:46 The Need for AI Literacy and Training

15:14 Shadow AI Usage and Organizational Risks

18:11 The Schism in the Workforce: Fast Lane vs. Slow Lane

21:00 Team Effectiveness vs. Individual Productivity

24:02 Governance and Communication in AI Adoption

29:20 Navigating AI Adoption in Organizations

32:20 The Importance of Communication and Collaboration

35:43 The Role of the Superworker

39:02 Mindset Shifts for AI Integration

43:41 Collective Intelligence and Team Dynamics

47:44 The Need for Storytelling in AI Communication

Kaz Hassan: https://www.linkedin.com/in/kazhassan

Unily: https://unily.com

AI Reality Check report: https://www.unily.com/resources/reports/the-ai-reality-check

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Substack: https://elevateyouraiq.substack.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, education, technology, higher education, online learning, ethics, policy, critical thinking, digital culture, workforce skills, creativity, innovation, personalized learning, workforce, digital natives

Takeaways

• AI is transforming education, similar to yet more widespread and complex than past technological shifts.
• Ethical policies are crucial for responsible AI integration.
• Students must learn to use technology responsibly.
• Digital natives have different expectations and experiences with technology.
• The speed of technological change in education is unprecedented.
• Faculty engagement is essential for successful AI integration.
• AI tools can provide authoritative responses, but critical thinking is necessary.
• The future of education will require ongoing adaptation, including AI literacy and policy development. 
• Creativity and curiosity in students should be nurtured through innovative projects.
• Higher education is being questioned for its ROI in today's job market.
• Personalized learning is essential for student success.
• Diversity in education includes cognitive and experiential diversity.
• AI ethics will become a critical compliance issue in the future.
• Students should be taught to use AI responsibly and ethically.
• There are many pathways to success beyond traditional college degrees.

Sound Bites

• "AI is changing the landscape of education."
• "The speed of change in education is dizzying."
• "AI ethics is the new compliance."
• "Let's train this generation right."
• "Education should meet students where they are."
• "Education is a sacred responsibility."
• "Kids are creative and curious."
• "There's so much incredible opportunity."
• "Life rarely works in a straight path."

Chapters

00:00 Introduction to AI in Education

03:10 The Evolution of Technology in Education

05:49 Navigating AI's Impact on Learning

09:03 Trust and Critical Thinking in the Age of AI

12:05 The Dichotomy of AI Use in Education

14:58 The Role of Parents and the Future of Education

18:12 Federal vs. State Control in Education

21:14 Adapting Higher Education to AI

23:57 The Future of Workforce Skills and Education

31:28 The Risks of AI Adoption

34:24 Education and AI Literacy

39:10 Creativity and Innovation in Education

46:20 The Changing Landscape of Higher Education

49:50 Personalized Learning and Diverse Pathways

David Hatami: https://www.linkedin.com/in/david-h-b288114

EduPolicy.ai

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, data literacy, ethics, education, critical thinking, curiosity, creativity, technology, trust, authenticity

Takeaways

• Ceci Dones is a hybrid professional in AI and data literacy.
• Understanding data quality is crucial for effective AI implementation.
• Curiosity, creativity, and critical thinking are essential skills in the AI era.
• Data literacy does not mean everyone must be a data scientist.
• AI should be used as a coach, not just a calculator.
• Young people have a clear understanding of fairness in technology.
• We must not lose our inherent sense of fairness as we mature.
• The future of AI is exciting yet uncertain.
• We are still in the early stages of understanding AI's impact.
• The conversation around AI ethics is becoming increasingly important.

Sound Bites

• "What does AI mean for organizations?"
• "Garbage in, garbage out."
• "Curiosity, creativity, critical thinking."
• "You don't have to be a data scientist."
• "We are still figuring this out."
• "We come pre-programmed with ideas of fairness."
• "How do we not lose the humanness?"
• "AI should be a coach, not a calculator."
• "This is all so exciting and terrifying."
• "It's only chapter one."

Chapters

00:00 Introduction to AI and Trust

02:47 The Journey of a Hybrid Professional

06:02 Data Literacy and AI Implementation

09:11 Curiosity, Creativity, and Critical Thinking

11:57 Navigating Data Literacy Without Overwhelm

18:10 The Role of AI in Education

22:04 AI Ethics and Responsibility

36:59 The Future of AI and Human Interaction

Ceci Dones: https://www.linkedin.com/in/ceciliadones

3 Standard Deviations: https://www.3standarddeviations.com/

What Is a CMO to Do With AI?: https://www.linkedin.com/newsletters/7182036727794909184/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI in the workplace, AI productivity, AI compliance, hiring bias, AI literacy, AI in HR, AI governance, responsible AI, AI ethics, workforce transformation, automation in hiring

Key Takeaways

• AI productivity is about more than speed—it’s about effectiveness – AI isn’t just about working faster, but also about better decision-making and finding insights.
• AI hiring bias is real – If AI is trained on biased data, it can create legal risks, discrimination issues, and adverse hiring outcomes.
• AI literacy is the next essential skill – Future job descriptions will require AI proficiency, just like Microsoft Office skills in the past.
• AI-driven businesses are coming – There may soon be billion-dollar companies run by just one person and their AI agents.
• AI governance is critical – Companies need to implement AI monitoring & compliance tools (like Warden AI) to ensure fair hiring practices.

Top Quotes

• "AI isn’t replacing humans—it’s forcing humans to redefine their roles."
• "AI productivity isn’t just about working faster—it’s about working smarter."
• "There’s a reason AI governance tools like Warden AI exist—because bias in AI hiring is real."
• "AI literacy will be the next ‘must-have’ skill in every job description."
• "We’re not far from the era of billion-dollar companies run by one person and their AI."

Chapters

00:00 – Challenges with AI-Powered Hiring: Bias & Compliance Risks

10:09 – AI Productivity vs. Human Productivity: Where’s the Balance?

20:34 – AI Literacy: The New Essential Skill for Employees

30:52 – AI Governance & Legal Risks in Hiring Tech

40:13 – Final Thoughts: AI’s Place in Hiring & Workforce Development

Jeremy Lyons: https://www.linkedin.com/in/lyonsjeremy

RecOps RoundUp: https://recops.substack.com/

RecOps Collective: https://www.recopscollective.com/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI in hiring, recruiting automation, mass applications, fake candidates, AI ethics, AI-assisted interviews, job applications, resume filtering, candidate experience, hiring intelligence

Key Takeaways

• Mass AI job applications are creating a hiring overload – Recruiters are struggling to handle huge spikes in applications as AI tools allow job seekers to apply at scale.
• Fake candidates are a growing concern – AI-assisted fraud is emerging, with candidates outsourcing interviews to others or using real-time AI assistance.
• AI-assisted interviews: Ethical or unfair? – Should candidates be allowed to use AI during an interview? Some view it as cheating, while others see it as resourcefulness.
• AI can improve the candidate experience—but only if used right – AI-powered interview tools could give every candidate a fair shot while reducing recruiter workloads.
• AI resume filtering is flawed – Many AI-driven Applicant Tracking Systems (ATS) may be rejecting great candidates due to flawed keyword screening.

Top Quotes

• "AI is making it easier to apply for jobs—but is it actually making it easier to get hired?"
• "If AI is being used in hiring, why shouldn’t candidates be allowed to use it in interviews?"
• "People are treating mass applications like it is a new problem. This is a problem that colleges have been dealing with for 20+ years."
• "Companies need to rethink how they screen candidates before AI makes the hiring process completely unmanageable."

Chapters & Timestamps

00:01 – Introduction to Jeremy Lyons & RecOps Collective

02:27 – The Recruiting Operations Conference & Building AI for TA

10:45 – AI in Hiring: The Rise of Mass Applications & Fake Candidates

19:36 – Ethics & Boundaries of AI Use in Job Interviews

30:24 – AI’s Role in Resume Filtering & Candidate Screening

45:17 – Challenges with AI-Powered Hiring: Bias & Compliance Risks

Jeremy Lyons: https://www.linkedin.com/in/lyonsjeremy

RecOps RoundUp: https://recops.substack.com/

RecOps Collective: https://www.recopscollective.com/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

Humanness, AI literacy, self-awareness, human value, VUCA, adaptability, human creativity, future of work, talent strategy, leadership, storytelling, human-centric AI

Highlights

• Mike’s Journey: From Navy service to filmmaking and leadership development
• The Rise of Humanness: Why expanding human value in the age of AI is essential
• VUCA and Adaptability: A framework for navigating rapid change in life and business
• Self-Awareness Exercises: How understanding yourself is key to success in AI-driven environments
• AI as a Teammate: How AI can augment creativity but not replace human intuition
• Authentic Relationships: Why human connection will remain central despite technological advancements
• Rethinking Career Paths: Moving beyond linear career trajectories by leveraging creativity and adaptability

Quotes

• “We’ve been training humans to be robots for the last 100 years. Now it’s time to pull the creator out of them.” — Mike Schindler
• “When the vision is big, the circumstances don’t matter.” — Mike Schindler
• “AI can help you see around corners, but you need the self-awareness to discern when its recommendations align with your goals.” — Mike Schindler
• “We need more wild ducks—people willing to carve their own path and challenge the status quo.” — Bob Pulver
• “Companies that don’t identify their moonshot and align their people toward it will struggle to remain relevant.” — Mike Schindler
• “AI is designed to be a collaborator, but humans bring the nuance, emotion, and intuition that make great storytelling.” — Mike Schindler

Chapters

[00:00] - Introduction: Meet Mike Schindler, Navy veteran turned filmmaker and leadership coach

[02:12] - Current Projects: The Rise of Humanness and Mike’s upcoming documentaries

[04:37] - What Is VUCA? Understanding volatility, uncertainty, complexity, and ambiguity

[07:40] - Teaching Humans to Be Human Again: Breaking free from robotic routines

[10:14] - Self-Awareness Exercises: How understanding yourself leads to growth and success

[14:03] - AI Ready, Human Ready, Change Ready: Preparing for a rapidly evolving future

[21:20] - Talent Strategy and Adaptability: Why job roles change faster than ever before

[29:18] - Rethinking Career Paths: How creativity and individuality are the keys to future success

[35:36] - Human Connection: Why authentic relationships are more important than ever

[44:55] - AI in Creativity: How AI assists in filmmaking and creative problem-solving

[51:33] - Final Thoughts: Building better relationships and rediscovering purpose

Mike Schindler: https://www.linkedin.com/in/mjschindler

VUCA MAX: https://itsvucamax.com/

The Rise of Humanness (podcast): https://riseofhumanness.podbean.com/

“The Rise of Humanness” (book): https://itsvucamax.com/book-2/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

HR technology, AI, generative AI, workforce optimization, cybersecurity, talent management, responsible AI, data privacy, offboarding, cognitive diversity, AI, hiring, diversity, responsible AI, HR, talent acquisition, data analytics, inclusivity, neurodiversity, technology transformation

Takeaways

• Jen Kirkwood has over 28 years of experience in HR technology and IT.
• She founded Talvana Consulting to focus on talent optimization.
• AI is rapidly changing the landscape of HR and IT.
• Transparency in AI systems is crucial for effective governance.
• Offboarding processes are often neglected but essential for alumni relations.
• Cognitive diversity is important in AI governance committees.
• HR must be involved in AI decision-making processes.
• Cybersecurity is a critical concern for HR data management.
• Inclusivity in hiring practices is vital for innovation.
• The future of work requires a focus on skill development and optimization. 
• Data analytics maturity is crucial for effective hiring practices.
• Historical bias in hiring data can perpetuate discrimination.
• Responsible AI can uncover overlooked talent pools.
• Organizations must prioritize AI ethics and governance.
• HR needs to articulate business cases for responsible AI.
• Neurodiversity can drive innovation and creativity.
• Flexibility in management is essential for diverse teams.
• Self-learning and digital literacy are key for organizational transformation.

Sound Bites

• "AI models need to be embedded in every use case."
• "AI is a team sport."
• "The complexity of AI regulations is overwhelming."
• "How do we hire more talented engineers?"
• "Responsible AI is how we get through this."
• "HR is the highest risk area."
• "We are all responsible for responsible AI."
• "You can't just cut everyone."
• "Flexibility is a treasure in management."

Chapters

00:00 Introduction to Jen Kirkwood and Her Journey

02:50 The Intersection of HR and IT in AI

06:12 Challenges and Opportunities in AI for HR

08:57 The Importance of Transparency and Governance in AI

12:04 Navigating Offboarding and Alumni Relations

15:07 The Role of Cognitive Diversity in AI Governance

18:05 Cybersecurity and Responsible AI Practices

21:08 The Future of Work and Talent Optimization

32:24 The Importance of Data in AI Hiring Practices

34:42 Responsible AI: A Path to Inclusivity

35:41 The Rapid Evolution of AI in HR

39:00 AI Ethics and Governance in Organizations

41:22 The Role of HR in Responsible AI Implementation

45:54 Transforming Organizations Through AI and Inclusivity

51:31 Harnessing Neurodiversity for Innovation

55:31 Balancing Technology and Human Talent

Jen Kirkwood: https://www.linkedin.com/in/jenphillipskirkwood/

Talvana Consulting: https://talvanaconsulting.com/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant, and trustworthy. 

Keywords

AI, HR, skills-based organizations, talent management, technology adoption, Jeff Wellstead, human resources, skills taxonomy, mid-sized companies, startup culture, HR, AI, workforce planning, performance assessment, skills taxonomy, talent intelligence, scenario planning, data-driven decision making, digital footprint, organizational change

Takeaways

• Jeff Wellstead has over 35 years of experience in HR, primarily in tech startups.
• He believes traditional HR practices need to be reinvented for modern workplaces.
• AI adoption in HR is still low, especially among mid-sized companies.
• Skills-based organizations focus on competencies rather than traditional job titles.
• AI can help create a skills taxonomy to better assess employee capabilities.
• AI is transforming how organizations manage talent and skills development.
• The integration of AI can lead to personalized learning and development paths.
• Companies need to be agile in adapting to new technologies and practices.
• Proper data is essential for making informed decisions about employee careers. 
• Data-driven decision-making can significantly enhance HR processes.
• AI can transform workforce planning and talent management.
• Scenario planning is essential for anticipating workforce gaps.
• AI agents can streamline HR functions and improve efficiency.
• HR professionals must adapt to the changing landscape of AI.
• The future of HR will involve a blend of technology and human interaction.
• HR must focus on coaching and development as AI takes over routine tasks.

Sound Bites

• "I'm not a big fan of traditional legacy HR."
• "I got to reinvent HR from scratch."
• "We need to rethink traditional roles and job titles."
• "AI can help create an intelligence skills taxonomy."
• "We need the right people in the right seats."
• "AI is actually much easier than it's ever been."
• "Don't be complacent in what you're doing."

Chapters

00:00 Introduction to Jeff Wellstead's Journey

02:56 Reinventing HR in Tech Startups

05:53 The Challenges of AI Adoption in HR

09:02 Building Skills-Based Organizations

11:58 The Importance of Skills Taxonomy

15:10 Leveraging AI for Talent Management

18:07 Navigating Skills Gaps and Future Roles

26:29 Performance Assessment and Digital Footprints

27:33 Data-Driven Decision Making in HR

29:53 The Role of AI in Workforce Planning

32:35 Scenario Planning and Skills Taxonomy

35:11 AI Agents and Talent Intelligence

38:25 AI's Impact on HR Roles and Responsibilities

43:41 The Future of HR with AI

Jeff Wellstead: http://uk.linkedin.com/in/jrwellstead/

Big Bear Partners: http://www.bigbearpartners.com

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

Reejig, AI, work ontologies, human-centric AI, workforce strategy, data-driven HR, skills-based organizations, automation, global innovation, AI, human skills, automation, workforce strategy, trust, organizational culture, upskilling, reskilling, critical thinking, innovation

Takeaways

• Reejig is focused on understanding the skills of the future.
• Work is being automated, not skills.
• Human-centric approaches can coexist with business-centric strategies.
• Data-driven decisions in HR are crucial for effective workforce planning.
• The speed to market is a key differentiator in business.
• AI and automation are reshaping the workforce landscape.
• Global innovation varies significantly due to regulations.
• Companies need to anticipate the needs of the business.
• Human-centric AI is essential for sustainable business practices.
• Understanding the digital worker's role is critical for future planning. Human skills are irreplaceable in the age of AI.
• Organizations must understand task exposure to automation.
• Building trust and transparency is crucial for employee engagement.
• A culture without fear encourages innovation and adaptation.
• Common language around skills is essential for organizational success.
• Upskilling and reskilling are necessary for future workers.
• AI can augment human capabilities, not replace them.
• The future of work involves collaboration between AI agents.
• Visibility into job roles helps in strategic decision-making.
• Innovation in AI can lead to new workforce strategies.

Sound Bites

• "We want a world with zero wasted potential."
• "The US continues to be the biggest market."
• "We need to think systemic, not linear."
• "What are you ready to automate?"
• "We need to create visibility and confidence."
• "It's about trust and transparency."
• "We need to equip organizations with data."
• "Culture without fear is essential."
• "We need a common language around skills."
• "This is a new variation of 'agency'."

Chapters

00:00 Introduction to Reejig and Nuno's Background

06:09 The Evolution of Work Ontologies

12:10 The Impact of AI and Automation on Work

18:11 Human-Centric AI and Business Strategy

24:08 Data-Driven Decision Making in HR

29:54 Global Perspectives on Innovation and Regulation

36:36 The Importance of Human Skills in the Age of AI

39:51 Navigating Automation: Understanding Task Exposure

44:32 Building Trust and Transparency in Organizations

49:44 The Role of Culture in Adapting to Change

54:53 Innovative AI Solutions: The Future of Workforce Strategy

Nuno Goncalves: https://www.linkedin.com/in/nuno-goncalves

Reejig: http://www.reejig.com

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

DEI, AI, bias mitigation, cognitive diversity, responsible AI, legislation, workforce, diversity strategy, workforce reskilling, augmented intelligence, human-centric AI, diversity and inclusion, responsible AI, bias mitigation, ethical AI, organizational change

Takeaways

• Political pressures have negatively impacted DEI initiatives.
• The removal of 'equity' from DEI discussions is concerning.
• Progress in AI and DEI is being made, but more is needed.
• Cognitive diversity enhances decision-making in organizations.
• Responsible AI requires accountability from vendors and organizations.
• Legislation is lagging behind technological advancements.
• The future of work will require re-skilling to keep pace with AI. 
• Organizations must invest in reskilling to adapt to AI advancements.
• AI can help uncover overlooked talent in hiring processes.
• Augmented intelligence should enhance human capabilities, not replace them.
• Human-centric AI is essential for ethical and responsible technology use.
• Many organizations are hesitant to embrace AI due to concerns about bias.
• AI can significantly improve diversity and inclusion efforts in hiring.
• Responsible AI practices are crucial for maintaining ethical standards.

Sound Bites

• "I'm chasing the word promise 365 days this year."
• "I'm all things people."
• "I believe that progress is being made."
• "Cognitive diversity is incredibly important."
• "You can use AI to unearth talent."
• "AI is augmenting your own capabilities."
• "AI is good for business."
• "We're building a manager intelligence platform."

Chapters

00:00 New Year Reflections and Words of the Year

01:48 Torin Ellis: Background and DEI Work

03:07 Reflections on 2024: Political Climate and DEI Challenges

06:45 AI's Role in DEI and Bias Mitigation

13:08 Cognitive Diversity and Its Importance

19:54 Responsible AI and Legislative Challenges

24:45 The Future of AI and Workforce Implications

31:45 AI's Role in Uncovering Hidden Talent

33:46 Augmented Intelligence vs. Automation

35:39 Human-Centric AI: Ethics and Responsibility

38:03 Understanding AI's Limitations and Bias

42:25 The Impact of AI on Diversity and Inclusion

45:50 The Need for Responsible AI Practices

49:48 Addressing Systemic Inequities with AI

51:20 Building a Better Future with AI

Torin Ellis: https://www.linkedin.com/in/torinellis

Torin Ellis Brand: https://torinellis.com/

Reducing Bias in HR Using AI: https://www.plum.io/report-reducing-bias-in-hr

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, automation, responsible AI, AI governance, human-in-the-loop, efficiency, small business AI, AI consulting, workflow automation, legal tech, real estate technology, CRM integration, data-driven decisions, ethical AI use, AI in startups, solopreneurship, custom GPTs, AI assistants, AI adoption.

Key Takeaways

• Avi's Journey: Transitioned from finance and law to AI consulting, focusing on small and medium-sized businesses.
• Human-in-the-Loop Approach: Critical for ensuring automation is accurate, ethical, and effective.
• AI in Real Estate: Significant potential exists for automating document-heavy tasks, such as contract review and title searches.
• Custom AI Tools: Avi builds custom GPTs as personal assistants to streamline workflows and save time.
• AI Governance: Emphasizes the importance of certifications like SOC 2 and ISO for data security and trust in AI tools.
• Starting Small: Avi recommends introducing AI incrementally to get businesses comfortable with the technology.
• Empowering Users: Avi educates clients to independently manage and adapt AI tools, ensuring long-term success.

Notable Quotes

• "Everyone should have a custom GPT—it's like having a second brain."
• "Automation isn't about replacing jobs; it's about amplifying human capability."
• "Small businesses often struggle to leverage AI responsibly, but with the right tools, they can operate ten times faster, better, and cheaper."
• "AI governance starts with trust—if you lose trust, you've lost everything."
• "Even with AI, the human element remains critical for oversight and ethical decision-making."

Chapters

00:00 - Introduction to Avi Hacker

01:30 - Avi's Background: From Law to AI

03:12 - Founding an AI Consulting Company

06:41 - AI Governance and Responsible Use

08:47 - Applying AI in Real Estate

11:47 - Workflow Automation and Custom GPTs

14:32 - Educating Clients on AI Integration

17:46 - AI for Document Review and Summarization

20:10 - Challenges of AI Context Windows

24:12 - Importance of Human-in-the-Loop Systems

25:43 - Future of AI: Autonomous AI Managers

36:57 - How to Connect with Avi Hacker

37:11 - Final Advice for AI Beginners

Avi Hacker: https://www.linkedin.com/in/avi-hacker

The AI Consulting Network: https://theaiconsultingnetwork.com/

The AI Daily Brief: https://avihacker.substack.com/

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, HR, skills-based organization, talent intelligence, soft skills, data integration, business strategy, workforce planning, automation, employee engagement, AI agents, HR technology, AI governance, organizational culture, data integrity, responsible AI, automation, talent intelligence, strategic workforce planning, AI in hiring

Takeaways

• Skills-based organizations focus on aligning skills with business needs.
• Understanding both HR and business perspectives is crucial for success.
• Soft skills play a significant role in team dynamics and effectiveness.
• Total talent intelligence integrates various data sources for better insights.
• Organizations must anticipate market shifts to remain competitive.
• HR should proactively provide data-driven insights to the business.
• AI can enhance the assessment of both hard and soft skills.
• AI agents are evolving to execute complex tasks previously thought to require human intervention.
• AI governance is essential to ensure responsible and ethical use of AI technologies.
• Data integrity and analytics maturity are foundational for successful AI applications.
• Organizations must take responsibility for how they deploy AI, ensuring it aligns with their culture and values.
• AI can enhance human capabilities and support better decision-making in hiring and talent management.
• The future of work will require adaptability and continuous learning from both individuals and organizations.
• Strategic workforce planning can benefit from AI by integrating various business inputs and data sources.

Sound Bites

• "How do you define skills-based organizations?"
• "Skills are like money in the bank account."
• "We need to anticipate market shifts."
• "AI can limit friction in HR processes."
• "AI governance is crucial for responsible use."
• "Data integrity is key to AI success."
• "We must be responsible in deploying AI."

Chapters

00:00 - Introduction and Background of Remy Glaisner

03:13 - Transitioning from Technical to HR Perspectives

05:57 - Understanding Skills-Based Organizations

08:59 - The Role of Skills in Business Strategy

12:02 - Navigating Skills Mapping and Organizational Needs

15:00 - The Importance of Soft Skills in Talent Management

18:10 - Integrating Total Talent Intelligence

21:05 - Challenges in Data Sharing and Collaboration

23:54 - The Future of HR in Intelligent Organizations

27:48 - The Evolution of AI Agents

30:32 - AI in HR: Reducing Friction and Enhancing Efficiency

34:36 - AI Governance: Ensuring Responsible Use

38:34 - The Role of AI in Organizational Culture

41:45 - Data Integrity: The Foundation of AI Success

46:42 - The Responsibility of AI Deployment

Remy Glaisner: https://www.linkedin.com/in/rglaisner

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Key Topics Discussed:

• AI and Organizational Change: The role of AI in workforce transformation and how it’s reshaping leadership, employee roles, and collaboration.
• Upskilling for the Future: Why continuous learning and fostering AI literacy are essential for both leaders and employees.
• Breaking Down Silos: Strategies to remove barriers to collaboration and align organizational goals in the age of AI.
• Responsible AI: The importance of governance, transparency, and ethical practices in implementing AI solutions.
• AI Augmentation vs. Automation: Real-world examples of using AI to enhance human capabilities, from creating content to personalized learning.
• Strategic Workforce Planning: How organizations can rethink processes, roles, and incentives to align with AI-driven opportunities.

Takeaways for Listeners:

• AI adoption requires cultural shifts, leadership alignment, and trust-building across all organizational levels.
• Continuous upskilling, including AI literacy and data literacy, is critical for staying ahead of technological advancements.
• Leaders must move from managing tasks to managing outcomes, leveraging AI to empower teams rather than micromanage.
• Organizations should focus on responsible AI practices, ensuring compliance, transparency, and inclusivity at every stage.
• Experimentation and hands-on learning with AI tools can drive innovation and help organizations unlock new opportunities.

Notable Quotes:

• Pauline James: “The importance of transparency and training to mitigate risks cannot be overstated.”
• David Creelman: “We need to experiment hands-on to learn what AI can and can’t do—this is critical for its integration.”
• Bob Pulver: “Leaders need to understand AI’s impact to make informed, data-driven decisions for their organizations.”

Chapters

00:00 – Welcome and Introductions

03:00 – AI in Workforce Transformation

06:45 – Leadership in the AI Era

10:30 – Breaking Silos for Collaboration

14:20 – Upskilling and AI Literacy

18:10 – AI Augmentation vs. Automation

22:35 – Lessons from Rapid Change

27:15 – Responsible AI and Governance

32:40 – Experimentation and AI Tools

37:50 – AI’s Rapid Evolution

43:25 – Strategic Workforce Planning with AI

48:00 – Final Thoughts and Upcoming Projects

For more resources, visit:

• Pauline’s company website: Anchor-HR
• David Creelman’s publications and insights: David Creelman
• Upcoming events: HR Gazette

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver

Elevate Your AIQ: https://elevateyouraiq.com

Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy. 

Keywords

AI, HR, performance management, customer experience, workforce planning, talent development, employee engagement, generational differences, data-driven insights, trust in AI, AI, hiring, transformation, emotional response, AI literacy, responsible AI, data literacy, change management, bias training, organizational change

Takeaways

• AI enhances performance management by promoting agile processes.
• Trust in AI tools is essential for successful HR integration.
• Feedback frequency is shifting towards continuous rather than annual reviews.
• The candidate experience is crucial for attracting talent.
• Generational differences impact employee expectations and experiences.
• AI can help reduce biases in performance evaluations.
• Investing in talent development is key for organizational success.
• AI tools can streamline HR processes and improve efficiency.
• The future of workforce planning relies on comprehensive data integration. 
• Emotional responses to change can impact engagement.
• Organizations must foster AI literacy among employees.
• Bias training must evolve to include AI considerations.
• Policies on AI use are essential for responsible implementation.
• Continuous evaluation of AI tools is necessary.
• Data literacy is foundational for effective AI use.
• Curiosity and education about AI should be ongoing.

Sound Bites

• "Trust in HR around AI still needs to be built"
• "Candidates desire feedback, not ghosting"
• "Understand the emotional response to change."
• "We need a whole new lens on bias training."
• "Responsibility by design is crucial."
• "You can't just grab any shiny object."
• "Let's not set the bar at just good enough."

Chapters

00:00 - Introduction to AI in HR

02:48 - The Evolution of Performance Management

05:47 - Building Trust in AI Tools

08:53 - The Human Touch in Recruitment

12:07 - Navigating Generational Differences in the Workforce

15:02 - Data-Driven Insights for Talent Management

17:55 - The Future of Workforce Planning

20:51 - Leveraging AI for Talent Development

25:52 - Hiring Beyond Bias: The Need for Objective Criteria

27:06 - Navigating Transformation: Challenges and Opportunities

29:51 - Understanding Emotional Responses to Change

33:30 - AI Literacy: Empowering Organizations and Individuals

35:49 - Responsible AI: Training and Policies for Ethical Use

38:53 - Evaluating AI Tools: The Importance of Critical Thinking

46:52 - The Interplay of Data Literacy and AI Literacy

Sarah Katherine Schmidt: https://www.linkedin.com/in/sarahkatherineschmidt

PeopleLogic: https://peoplelogic.ai

For advisory work and marketing inquiries:

Bob Pulver: https://linkedin.com/in/bobpulver