Elevate Your AIQ

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Bob Pulver is helping each of us navigate our respective journeys with artificial intelligence (AI) effectively and responsibly. Bob chats with AI and Future of Work experts, talent and transformation leaders, and practitioners who provide diverse perspectives on how AI is solving real-world challenges and driving responsible innovation.

  1. 4 DAYS AGO

    Cultivating Curiosity and Amplifying Human Knowledge with Bob Danna

    Bob Danna, physicist, naval officer, former Senior Managing Director at Deloitte Consulting and Bersin by Deloitte, and author of the memoir "My Curious Life," joins host Bob Pulver for a wide-ranging conversation about a lifetime at the frontier of science and technology. Bob traces his journey from slide rules and nuclear reactors to agentic AI, sharing how he and collaborator Joe DiDonato built "Bot-Bob," a digital twin trained on his memoir, writings, and decades of experience. The conversation explores what digital twins can mean for knowledge workers, legacy building, and collective intelligence, including a live mastermind experiment where multiple digital twins, plus a digital Mark Twain, fielded questions from a live audience. Bob closes with an urgent call to bring more diverse human voices into AI development before the decisions that shape civilization get made without them. Keywords Bob Danna, digital twin, agentic AI, Bot-Bob, Joe DiDonato, My Curious Life, knowledge worker, collective intelligence, co-intelligence, legacy, mastermind, ElevenLabs, nuclear warfare, responsible AI, human centricity, future of work, STEM, Deloitte, memoir, Substack Takeaways Curiosity is the connective tissue of Bob's entire career, from nuclear physics and naval service to Deloitte consulting and digital twins, and he positions it as the essential human quality that AI can amplify but never replicate  A digital twin is far more than a knowledge repository; it encodes values, judgment, and personality, making it a genuine extension of a person's thinking The "mastermind" format, where multiple digital twins deliberate together in real time, opens new possibilities for accessing cognitive diversity without scheduling constraints When AI models are trained by a narrow group (such as military strategists), the outputs reflect that bias, making diverse human representation in AI development a matter of consequence Knowledge workers who collaborate with their own digital twins can operate at dramatically higher capacity and quality, not by being replaced, but by being amplified A responsibly built digital twin can preserve the wisdom, voice, and values of an individual for future generations Quotes "I'm just a curious guy. No matter what I'm into, I'm always looking at other things."  "When we free up tasks that human beings were doing, I think that is very, very positive. The real question is, what does the human being step up to do that only a human being can do?" "The definition of a knowledge worker is going to change. It's going to be that human being collaborating with the digital twin of that person." "It's very timely right now that we really start to have human conversations before we go down the path too far." Chapters 00:03 Welcome and introductions 01:21 Bob Danna's fascinating career journey 03:27 Early encounters with AI and neural networks 07:21 What makes us human, the evolution of calculators and computers 10:26 Joe DiDonato, soul-sinking, and the origin of Bot-Bob 14:41 Building Bot-Bob, memoir, voice, and guardrails 17:17 From chatbots to agents to digital twins, a practical framework 25:27 Brainstorming mode and collaborating with your own twin 28:16 Digital twins in consulting and the future of knowledge work 35:20 The mastermind experiment, Bot-Bob, Robo Lacey, and digital Mark Twain 41:14 AI, nuclear war scenarios, and the dangers of narrow training data 51:31 The workforce of 2030 and what it means to be a knowledge worker 58:55 Closing thoughts and how to connect with Bob Danna Bob Danna: https://bobdanna.substack.com/ “My Curious Life”: https://mycuriouslife.net/ For advisory work and marketing inquiries: Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

    58 min

  2. 1 MAY

    Evolving the HR Function Through Agentic AI and Human Potential with Laura Maffucci

    Bob Pulver sits down with Laura Maffucci, Head of HR at Globalization Partners, for a wide-ranging conversation on AI adoption, global workforce trends, and the evolving role of HR. Laura shares how G-P is deploying its agentic AI product, GIA, both externally for global employment compliance and internally as a pilot HR agent, while emphasizing the importance of grounding AI in trusted, expert-sourced data. They explore the growing disconnect between executive optimism and employee sentiment around AI, the durable human skills that matter most in an AI-augmented workplace, and why AI adoption without a clear problem to solve is a recipe for costly confusion. Laura also shares candid reflections on her own AI learning journey and what she sees ahead for the HR function. Keywords Laura Maffucci, Globalization Partners, GIA, employer of record, EOR, agentic AI, global employment, AI compliance, HR transformation, AI adoption, employee sentiment, AI literacy, early career roles, talent acquisition, deep fakes, AI governance, critical thinking, human skills, learning agility, shadow AI, AI Awesomeness Awards, internal mobility, cognitive diversity, compensation analytics, AI readiness, Gemini, NotebookLM Takeaways GIA has evolved from a compliance Q&A tool into an agentic platform that can generate contracts, audit company policies, and is now being piloted as an internal HR agent handling employee ticket inquiries The data behind GIA is grounded in over a decade of G-P's global employment expertise, offering a trusted alternative to general-purpose LLMs drawing from unverified internet sources A significant perception gap exists between executives who believe AI is driving efficiency and employees who feel it is actually adding to their workload or generating unreliable output they must clean up Entry-level roles are shifting toward managing and directing AI agents rather than executing tasks directly, with "taste" (the ability to evaluate AI output) emerging as a critical early-career skill Workforce hiring criteria must increasingly prioritize unteachable human attributes such as curiosity, learning agility, courage, and the willingness to relinquish control, because technical AI skills can be taught but these cannot AI adoption mandates without a clearly defined problem to solve create fragmented, siloed "shadow AI" that can undermine organizational strategy rather than advance it HR functions are being asked to lead organizational AI transformation without adequate resources, technical support, or direction, making the role both high-opportunity and genuinely demanding Assessing real AI usage requires creative mechanisms: GP uses a Slack sharing channel, quarterly performance check-in questions, and monthly AI Awesomeness Awards to surface how people are actually applying the technology Quotes "I know that when these things come out, whether you like them or not, you had best learn them and learn how to work with them." "If you have a legal or compliance question, I hope Reddit's not your first stop to get that answer." "You can't embrace AI and be a control freak. You have to be willing to let something go and let something do something." "The pitfall that I can see so many companies falling into is, we don't need people because we've got the AI to do this." "Being in HR right now is not for the weak. That I will say, for sure." "It should always be: what problem are we trying to solve? Because that's actually one of the biggest issues with AI." Chapters 00:02 Welcome and guest introduction 01:40 Employer of record explained 03:03 GIA overview and new agentic capabilities 05:27 Responsible AI and the importance of trusted data sources 08:47 GP research findings on AI adoption and executive-employee sentiment gap 11:50 AI as added burden vs. efficiency driver 13:45 Redefining early career roles in an agentic world 15:42 The human cost of replacing workers instead of augmenting them 19:05 The problem with AI mandates that skip the "why" 22:44 Human skills that matter most when hiring for an AI-augmented workforce 26:37 The AI-versus-AI problem in talent acquisition 27:39 Deep fakes, virtual interview integrity, and human oversight in TA 31:53 The evolving role of HR as a strategic function 37:13 C-suite dynamics and running HR as a pilot for GIA 39:27 Building an AI council, sharing culture, and identifying shadow AI 42:15 Measuring AI fluency through awards, check-ins, and community 45:14 Laura's personal AI journey and closing thoughts Laura Maffucci: https://www.linkedin.com/in/laura-maffucci G-P: https://www.globalization-partners.com/ For advisory work and marketing inquiries: Bob Pulver:⁠⁠ https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ https://elevateyouraiq.com⁠⁠⁠Substack: ⁠https://elevateyouraiq.substack.com⁠

    52 min

  3. 24 APR

    Humanizing the Hiring Experience and Earning Candidate Trust with Jerry Jao

    Bob Pulver is joined by Jerry Jao, CEO of Employ, who brings a perspective shaped by years of building AI-driven consumer personalization before turning that lens on hiring. Jerry shares how he is restructuring Employ for greater agility, how Pillar's interview and screening companions are reducing friction for job seekers and recruiters alike, and why the surge in AI-assisted applications is complicating matching on both sides. He also addresses candidate fraud and deepfakes, and explains how Employ's IBM partnership helps reduce bias and hallucinations across nearly 100 million applications processed annually. 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.com⁠⁠⁠Substack: ⁠https://elevateyouraiq.substack.com⁠

    44 min

  4. 17 APR

    Redesigning Work and Workforce Strategy for the Agentic Era with Paul Rubenstein

    Paul Rubenstein, Chief Evangelist and Talent Strategist at Visier, brings deep expertise in people analytics and workforce strategy to this wide-ranging conversation with Bob Pulver. He introduces a three-curves framework for CHROs navigating AI: the human-machine efficiency frontier, the ROI curve, and the humanity index. The discussion explores why workforce planning is having a long-overdue resurgence, and how HR can use AI-powered analytics to reach managers proactively rather than waiting for them to come to HR. Bob and Paul also examine the courage gap in AI adoption, the governance tension between restricting data and enabling better AI answers, and the design-plan-operate mindset required to truly transform work. 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

    55 min

  5. 10 APR

    Leading with Business Strategy to Deliver Sustainable AI Value with Charlene Li

    Charlene Li, analyst, author, and disruptive leadership expert, returns to Elevate Your AIQ to discuss with Bob her newly released book Winning with AI, co-authored with Dr. Katia Walsh. Charlene makes the case that most organizations are failing with AI because they treat it as a technology initiative rather than a strategic one — and lays out a 90-day, 12-step framework for building a foundation that creates real enterprise value. The conversation revisits themes from her Fall 2024 appearance, including responsible AI and the human-AI partnership, and explores how the landscape has evolved. Key topics include AI fluency as an organizational imperative, workforce reinvestment over workforce reduction, and the emerging concept of integrated intelligence — where human and AI capabilities combine to create something genuinely superhuman. 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

    1hr 1min

  6. 3 APR

    Architecting the Human-AI Partnership to Turn AI Strategy into Results with Oded Dubovsky

    Bob Pulver reconnects with former IBM colleague Oded Dubovsky, founder of STRAIX (Strategy for AI Execution), an advisory practice helping organizations adopt AI thoughtfully and effectively. Oded shares a career journey spanning over two decades at IBM Research's Haifa Lab — where he led pioneering cognitive computing and computer vision projects — through applied AI work at Intel, and into independent consulting. The conversation explores why 95% of organizations struggle to move beyond AI aspiration to real execution, and what it takes to build a solid foundation before layering in AI. Bob and Oded also reflect on the enduring value of human ingenuity, originality, and orchestration in an increasingly AI-assisted world. 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

    55 min

  7. 27 MAR

    Building and Managing AI Agents to Shape the Future of Work with Jacob Bank

    Bob Pulver sits down with Jacob Bank, Co-founder and CEO of Relay.app, whose career arc — from Stanford's Multi-Agent Systems Lab to founding Timeful (acquired by Google in 2015) to leading Gmail and Google Calendar product teams — represents one of the most continuous threads in AI agent development. Jacob frames AI agents not as software to configure, but as employees to hire, coach, and manage, arguing that great people managers are naturally suited to the AI era. He maps out a three-tier AI stack everyone should adopt and explores how knowledge work will be restructured, why AI literacy is non-negotiable, and how small businesses can now compete at scales once unimaginable. 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.com⁠⁠⁠Substack: ⁠https://elevateyouraiq.substack.com⁠

    53 min

  8. 20 MAR

    Rewiring Organizations for Human-Centric AI Transformation with Melissa Reeve

    Bob Pulver and Melissa Reeve explore AI transformation and organizational design through the lens of Melissa's Hyperadaptive framework. They unpack what it means to become AI native, why most enterprises stumble by neglecting human support structures, and how governance, AI activation hubs, and AI leads create always-on learning organizations. The conversation tackles the reinvestment dilemma — what to do with capacity freed by AI — and makes the case for durable skills, systems thinking, and career lattices over ladders. Both Bob and Melissa draw on their non-linear careers and share the belief that humans remain essential connective tissue in any AI-powered future. 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

    52 min
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About

Bob Pulver is helping each of us navigate our respective journeys with artificial intelligence (AI) effectively and responsibly. Bob chats with AI and Future of Work experts, talent and transformation leaders, and practitioners who provide diverse perspectives on how AI is solving real-world challenges and driving responsible innovation.

Information

  • Channel
    WRKdefined
  • Creator
    WRKdefined Podcast Network
  • Years Active
    2024 - 2026
  • Episodes
    117
  • Rating
    Clean
  • Copyright
    © All rights reserved by WRKdefined
  • Show Website
    Elevate Your AIQ

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