Elevate Your AIQ

Bob Pulver speaks with Agi Garaba, Chief People Officer at UiPath, about the organization’s evolution from robotic process automation (RPA) to agentic AI and how that has impacted people, processes, and culture. Agi shares how HR can lead with a human-centric lens during AI transformation, the importance of AI literacy, and the practical steps UiPath is taking to balance innovation with responsible governance. This conversation blends strategic foresight with pragmatic execution and offers a roadmap for any leader navigating AI-enabled change. 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

In this compelling episode, Bob speaks with Lisa Yokana, a pioneering educator and global consultant, about how AI is reshaping the education landscape. Lisa shares her journey from traditional art and architecture teacher to building an experiential design lab, STEAM program, and social entrepreneurship course. Bob and Lisa explore how AI can serve as a catalyst for changing not just what we teach, but how we teach and why. With a focus on student agency, lifelong learning, and the shifting expectations of the future workforce, Lisa offers practical insights and inspiration for educators, parents, and community leaders looking to bring relevance, equity, and innovation into the classroom. 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

Bob Pulver welcomes Ben Zweig, CEO of Revelio Labs and labor economist, for a deep dive into the evolving world of workforce analytics. Drawing from their overlapping experiences at IBM, Bob and Ben explore how the early days of cognitive computing sparked a journey toward greater transparency in labor market data. Ben explains how Revelio Labs is building a “Bloomberg Terminal” for workforce insights—grounded in publicly available data and powered by sophisticated taxonomies of occupations, tasks, and skills. Together, they examine the importance of job architecture, the promise and pitfalls of AI in workforce analytics, and the complexities of measuring contingent and freelance labor. Ben also shares a preview of his upcoming book, Job Architecture, and how LLMs are being used to redefine how organizations model and respond to changes in work itself. 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

Bob Pulver speaks with Emily Scace, Senior Legal Editor at Brightmine, about the intersection of AI, employment discrimination, and the evolving legal landscape. Emily shares insights on how federal, state, and global regulations are addressing bias in AI-driven hiring processes, the responsibilities employers and vendors face, and high-profile lawsuits shaping the conversation. They also discuss candidate experience, transparency, and the role of AI in pay equity and workforce fairness. 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

Bob speaks with Brandon Roberts, VP of Global People Product, Analytics, and AI at ServiceNow. Brandon shares how ServiceNow is navigating AI transformation from within its HR organization, balancing internal experimentation with client-informed innovation. They dive deep into responsible AI practices, strategic reskilling, and cross-functional collaboration, while unpacking key frameworks. Brandon also offers a preview of forthcoming research on the future impact of agentic AI on the workforce and shares actionable insights for HR and business leaders on how to lead with confidence, empathy, and clarity in a rapidly evolving landscape. 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

Bob sits down with Cole Napper, VP of Research, Innovation & Talent Insights at Lightcast, to unpack the complex and rapidly evolving world of people analytics. From his eclectic career across industries to his recent book release and his co-hosting role on the very popular people analytics podcast, Directionally Correct, Cole shares practical insights and hard-earned wisdom on topics like AI readiness, org network analysis, and the intersection of data, influence, and leadership. Bob and Cole explore the paradoxes of the HR tech ecosystem, the stubborn persistence of unsolved problems, and why storytelling with data is really about persuasion. Cole also gets candid about the ethical responsibilities facing those who wield data, and why the future of workforce planning demands a complete rethink of how we study work itself. 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

In this wide-ranging and thought-provoking conversation, Bob Pulver sits down with Steve Levy — recruiting veteran, technologist, and self-proclaimed “truth-teller” — to explore how talent, technology, and transformation intersect in today’s world of work. From the early days of expert systems and green-screen mainframes to the complexities of generative AI, Steve brings a rare blend of historical context, critical thinking, and humor. Together, they tackle topics like the ethics of candidate AI, bias in hiring platforms, skills-based hiring, the need for AI literacy, and why every recruiter needs to be more curious — and more human. Steve also shares lessons from his decades as a lifeguard at Jones Beach, and how that role shaped his instincts for protecting and empowering people — a theme that carries through everything he does in talent acquisition. 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

In this lively and thought-provoking episode of Elevate Your AIQ, Bob Pulver reconnects with former collaborator and pioneering technologist Marshall Kirkpatrick. From their early work intersecting social data and influence to Marshall's latest AI-driven workflows, the conversation explores how human insight and machine intelligence are converging. Marshall shares real-world examples of using synthetic personas, market monitoring systems, and creative prompting strategies to uncover early signals, amplify strategic decisions, and reimagine everything from talent acquisition to environmental policy tracking. It's a conversation that navigates the emergence of machine learning for social insights to the frontier of AI innovation. 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

Bob sits down with Colette Mason, a tech veteran with 40 years of experience in computing and a deep understanding of human behavior through her work in coaching and neuro-linguistic programming. Together, they explore the hype and reality around AI adoption, automation myths, and why “responsible by design” is more than just a catchphrase. Colette shares her perspectives on human-centric design, AI literacy, and how to keep authenticity intact in an AI-powered world. With warmth, humor, and real-world wisdom, this conversation brings clarity to an often-confusing landscape—and reminds us that technology should augment rather than replace what only humans can and should do. 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

Bob sits down with Dan Stradtman, Chief Marketing Officer at Bloomfire, to explore the evolving landscape of knowledge management (KM) in the age of AI. Dan brings a wealth of experience from Fortune 500 giants like Walmart, GE, and Lubrizol (Berkshire Hathaway). They discuss how often tacit and institutional knowledge is undervalued and underutilized. Bob and Dan unpack Bloomfire’s concept of “Enterprise Intelligence” and its new framework for treating knowledge as a measurable, strategic asset. They also cover the risks of overlooking tacit knowledge, how AI adoption is changing who leads knowledge initiatives, and the crucial role of ethics, trust, culture, and human-centricity in the enterprise AI journey. 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

Bob Pulver and Casey Fox discuss the evolution of Tekletics, a company focused on bridging the gap between untapped talent and technology careers. Casey shares his journey from a business major to the CTO of Tekletics, emphasizing the importance of work ethic, innate human skills, and the role of AI in talent acquisition and development. They explore the challenges and opportunities presented by AI in the workforce, the need for a culture of responsibility, and the importance of human potential in the age of automation and AI. 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

Bob Pulver sits down with Siadhal Magos, CEO and Co-founder of Metaview, to explore how AI can unlock a more structured, scalable, and insight-rich approach to hiring. Siadhal brings deep experience from the world of product and people to unpack why interviews—despite being central to business success—remain one of the most inconsistent and intuition-driven processes in organizations. 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

Bob Pulver talks with Kristi Broom, Co-founder of Rising Tide Cooperative and a seasoned transformation leader. Kristi's career has spanned EdTech, L&D, operations, and HR. She shares her journey from building early learning platforms to leading organizational change at scale—all while staying grounded in her passion for helping people grow. The conversation explores what it means to be a generalist in an era of specialization, how to design systems that support behavior change, and the role of curiosity, structure, and storytelling in navigating innovation. Whether you’re working in HR, technology, transformation, or operations, this episode offers a fresh perspective on what it really takes to lead through complexity and build a future-ready organization. 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

Bob Pulver welcomes Andrew Gadomski, Founder and Managing Director of Aspen Analytics, to talk about how AI and data science are reshaping the future of HR, talent, and organizational decision-making. Andrew is a veteran workforce data strategist who shares candid, practical insights on what it really takes for companies to evolve their data maturity, why LLMs can’t be treated like magic wands or oracles, and how to make AI work with your people, not instead of them. From “decision gravity” to the fallacy of talent pipeline management, this episode is a masterclass in balancing technological possibility with human nuance. 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

Bob Pulver chats with Chris Maurio, Vice President of the Oracle solutions practice at Argano, about the evolution of HR technology, the role of AI in enterprise transformation, and the importance of human-centric approaches in AI governance and ethics. They discuss the need for AI literacy in education and the significance of community in fostering collaboration and learning. The conversation emphasizes the balance between technology and human interaction, the future of AI in education, and the importance of curiosity in learning AI. 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.

Bob Pulver hosts Michael Palys and Mike Patchen, Co-founders of Colleva, to discuss the innovative use of AI in coaching and talent acquisition. They explore the evolution of AI coaching, its applications across various industries, and the importance of addressing AI bias. The discussion highlights the potential of AI to enhance employee training, improve sales performance, and streamline recruitment processes, while emphasizing the need for responsible AI governance. The conversation concludes with insights into upcoming events and the future of AI in the workplace. 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.

Bob Pulver chats with Adam Jackson, Founder and CEO of Braintrust, about the evolution of AI in recruitment, the importance of trustworthy technology, and the future of the job market. They discuss the user experience of AI interviews, the necessity of human oversight, and the skills needed for the future workforce. Adam shares insights on how AI can streamline recruitment processes and the challenges organizations face in adopting these technologies. 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.

Bob Pulver sits down with Joel Zeff, who shares his unique journey from journalism to improv comedy and keynote speaking. They explore the importance of adaptability, the role of fun in the workplace, and how improv can teach valuable lessons about change and teamwork. Joel discusses his recent book, which encapsulates these themes, and emphasizes the need for individuals to embrace their potential in the face of change. Bob and Joel also explore the themes of human potential, leadership, and the integration of AI in the workplace. They discuss the importance of embracing change, the role of leaders in fostering team success, and the necessity of human skills in an increasingly automated world. The dialogue emphasizes the need for flexibility, adaptability, and the freedom to make mistakes as essential components of personal and professional growth. 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.

Keywords 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.

Bob sits down with Dr. Anna Tavis, a leader in human capital management and higher education. They discuss the evolution of HR skills, the impact of AI on education, and the importance of personalized learning. Dr. Tavis emphasizes the need for educational institutions to adapt to the changing landscape and prepare students for future challenges. The conversation also touches on the role of technology in coaching and mentorship, and the necessity of developing critical thinking skills in learners. Anna and Bob discuss how data-driven feedback can enhance learning and performance, the importance of trust in AI coaching, and the evolving role of universities in preparing students for a dynamic job market. They emphasize the need for continuous learning and adaptability in an increasingly automated world, while addressing concerns about job displacement and the importance of human connection in the workplace. 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.