Elevate Your AIQ

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.

Elevate Your AIQ is a business podcast hosted by Unknown Host, with 136 episodes on record and a Required Pod Score of 80.

Unknown Host hosts Elevate Your AIQ, a business show with 136 episodes published.

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  Elevate Your AIQ

  Ep 137: Trading AI Hype for Evidence and Education in Talent Tech with Hayley Skivington

  Sep 25, 202659 min

  Hayley Skivington began her career in recruitment and has come full circle as Head of Product at Oleeo, where she sits at the intersection of product vision, commercial strategy, and the realities recruiters face every day. In this conversation with Bob, she explains why her role has expanded well beyond building features: with fear of job loss, litigation, and getting it wrong still widespread, vendors now have to hold customers' hands as educators and trusted advisors. The two dig into what responsible AI looks like in practice for a company serving government, policing, and financial services, and how Oleeo competes in a crowded market where ERPs, HCM suites, and AI startups all want a piece of recruiting. Hayley also offers an inside look at how Oleeo builds AI fluency across its own workforce, and Bob draws parallels to the early days of corporate social media bans. They close by looking ahead at how recruiters' work and skills will change as their tools become more connected. Keywords Hayley Skivington, Oleeo, responsible AI, explainability, talent acquisition, applicant tracking systems, AI literacy, candidate experience, EU AI Act, ISO 42001, vendor evaluation, shadow AI, Police Scotland, interoperability, cultural alignment, recruiter upskilling Takeaways Surfacing the evidence behind AI screening decisions gives recruiters confidence and gives candidates feedback to improve future applications. Buyers adding AI features increasingly need sign-off from security and IT compliance, so vendors should equip them with ready-made documentation. Integrating with existing systems like Oracle can deliver AI value without the cost and upheaval of replacing an ATS. Police Scotland went from treating any AI use as cheating to cutting email inquiries by roughly 30% within weeks, freeing time for candidates navigating medicals and vetting. Lunch hackathons and peer-led sessions spread practical AI know-how faster than formal training alone. Hayley expects recruiting tools to converge with collaboration and analytics platforms, pulling HR, talent management, and talent acquisition closer together. Recruiters should build skills in managing knowledge bases, evaluating compliance risk, and handling candidate appeals. Quotes Whenever anybody comes to us with anything, we always say, what's the problem? What are we trying to fix? You don't need to rip everything out. We can complement your technology stack, but help you solve that problem that you've got that your current technology can't do. We run a thing called the AI Forum and that's all about education. I'm not going there to talk about my latest product or why you all need to buy it from me. Those simple tools... can be the light bulb moments in organizations that are really risk averse because a chat bot feels quite friendly, right? People become strangely fond of whichever tool they're using the most. My advice to recruiters is to be AI literate. Think about how you leverage AI within your role and really start to upskill yourself. Chapters 00:01 Welcome and introductions 00:51 Hayley's path from recruitment to head of product 05:23 Building AI on strong foundations, not band-aids 09:06 Showing recruiters and candidates the evidence behind AI 13:29 Leveling the playing field and learning AI at home 18:43 Regulations, vendor evaluation, and shared responsibility 25:55 Competing in a crowded talent tech market 33:10 AI literacy inside Oleeo and the AI Forum 42:33 Police Scotland's journey from AI ban to adoption 45:20 Why banning AI leads to shadow AI 53:06 The evolving role of the recruiter Hayley Skivington: https://www.linkedin.com/in/hayley-skivington-63217531/ Oleeo: https://www.oleeo.com/ For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

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  Elevate Your AIQ

  Ep 136: Measuring Belonging to Strengthen Human Infrastructure with Eric Knauf

  Sep 18, 20261 hour

  Bob sits down with Eric Knauf, founder of BelongHQ and author of The 56% Solution: How Belonging Infrastructure Transforms Performance, who traces his path from studying organizational psychology to leading talent through a company's 55% reduction in force and a historically low employee net promoter score (eNPS). That turnaround became the origin of his belonging framework: five measurable pillars, psychological safety, inclusion, support, connection, and purpose, each with a direct, causal tie to business outcomes like innovation, retention, and profitability. The conversation moves from operationalizing belonging inside real organizations to why most AI transformations are already failing before they start, and how the health of an organization's human infrastructure predicts its readiness for change. Eric and Bob dig into what it takes to close the gap between a company's best and worst managers, and why fixing that gap costs commitment rather than money. Keywords belonging, psychological safety, organizational health, human infrastructure, employee engagement, reduction in force, eNPS, talent leadership, AI transformation, change management, Deloitte, BetterUp, Amy Edmondson, frontline managers, inclusion, connection, purpose, The 56% Solution, BelongHQ, workforce analytics, retention, M&A due diligence Takeaways Filling a role isn't the same as creating value, and talent leaders should map where value is actually created before optimizing headcount A 55% reduction in force and an eNPS of negative 73 became the origin story for Eric's belonging framework, which pulled that same team's score to positive 8 within six months Deming's finding that 94% of performance variance sits inside the system, not the individual, reframes culture as an engineering problem rather than a personality problem Belonging breaks into five measurable pillars, psychological safety, inclusion, support, connection, and purpose, each tied to a specific, causal business outcome Averages hide the real risk. The gap between an organization's strongest and weakest frontline managers predicts far more than a single companywide engagement score Psychological safety is the top predictor of whether employees actually use AI tools, according to a 2,250 person study Eric cites in the conversation Only seven cents of every AI investment dollar reportedly goes toward people, even as 88% of AI initiatives fall short of plan Strengthening human infrastructure costs commitment and ego, not budget, and pays off in retention, innovation throughput, and even M&A due diligence Quotes "It's one thing to fill a role. It's another thing for that human to actually add value." "It was stated that 88% of AI initiatives are not going as planned." "Ninety-three cents on the dollar are going to AI to the technology itself. Only seven cents on the dollar are going to the people." "The number one predictor of whether or not they use AI, psychological safety." "It requires being more human. It requires five things: psychological safety, inclusion, support, connection, and purpose." "To improve those metrics doesn't require a lot. It requires being a better person." Chapters 00:02 Welcome and introduction of Eric Knauf 00:36 Eric's roots in organizational psychology and path into talent leadership 02:54 Filling roles versus creating value, lessons from lean consulting 05:12 A brutal turnaround, leading a company through a 55% reduction in force 07:40 From negative to positive, the swing that led to writing a book 10:48 Systems versus people, and where the epiphany began 12:12 Discovering belonging, the Deming principle and the BetterUp research 16:30 Defining belonging, five pillars and why CFOs need proof, not emotion 20:31 Culture and engagement as outcomes, not goals in themselves 27:12 Operationalizing belonging infrastructure inside an organization 29:43 Why most AI transformations are already starting on the wrong foot 33:27 Psychological safety as the top predictor of AI adoption 45:14 Psychological safety failures at the C-suite level 49:14 Writing for the CFO, the skeptic, and the human side 59:00 Closing advice, know where you stand before you chase where you're going Eric Knauf: https://www.linkedin.com/in/eknauf BelongHQ: https://belonghq.com/ The 56% Solution: https://a.co/d/06xUAVmy For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

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  Elevate Your AIQ

  Ep 135: Assessing and Evolving Human-Centric AI Readiness with Tracy St.Dic

  Sep 11, 202651 min

  Tracy St.Dic, VP of Global Talent at Zapier, joins Bob to talk about what it actually takes to build an AI-fluent workforce, drawing on her fifteen years in education, including a stint leading national recruitment at Teach for America, before joining Zapier. She walks through the origin and evolution of Zapier's AI fluency rubric, the difference between AI adoption and true AI transformation, and why she still rates her own company a four out of ten. The conversation covers how Zapier is reshaping the recruiter role into more of a talent advisor function, freeing people from busywork to focus on coaching and relationship-building, and the internal AI workbench her team is building to support that shift. Tracy and Bob also dig into the risk of companies blaming headcount reductions on AI when the real driver is a search for different skills, and why hiring for trajectory, not a static skill snapshot, matters more than ever. Keywords AI fluency, talent transformation, Zapier, Teach for America, AI adoption, AI transformation, citizen development, talent advisors, workforce upskilling, hiring philosophy, agent harness, slope over snapshot, human-centric AI, quality efficiency employee experience, responsible AI Takeaways Zapier's AI fluency rubric has four pillars: mindset, strategy, building skills, and accountability, and it applies to both hiring and internal development. Tracy distinguishes AI adoption (bolting AI onto existing workflows) from AI transformation (redesigning work from the ground up), and rates Zapier a four out of ten on that scale. A simple test for any AI initiative: does it improve quality, efficiency, and employee experience, not just speed. Leaders need to define a clear vision for their function before scaling citizen development, or teams end up building in inconsistent directions. Zapier is shifting recruiters toward a "talent advisor" role, using AI to handle research and reporting so people can focus on coaching and relationship-building. Blaming headcount reductions solely on AI is often inaccurate; the real driver is companies wanting different, more AI-fluent talent. Zapier hires for "slope over snapshot," prioritizing a candidate's trajectory and rate of learning over current tool proficiency. The talent team is building an internal "TA workbench" inside an agent harness (Claude Code) to centralize context and best practices for recruiters. Quotes "Brilliance is distributed everywhere and opportunity is not." "You can delegate the task, but not the accountability." "Even if the technology isn't there yet, eventually it will be. And then you'll be ready for it." "We're not hiring people for just what they know today. We want to hire people for the trajectory at which they climb." "It's a very small percentage of companies that are seeing real ROI with AI right now." "Their company's philosophy is to keep what you kill." Chapters 00:02 Welcome and introduction to Tracy St.Dic 00:32 Tracy's path from Teach for America to VP of Global Talent at Zapier 02:06 Why access and democratization shaped her career 05:28 Origins of Zapier's AI fluency rubric and its four pillars 11:59 AI adoption versus AI transformation 16:22 A simple framework: quality, efficiency, and employee experience 19:43 Why leaders need a vision before scaling citizen development 24:02 Updating the rubric as AI fluency rises company-wide 27:14 Turning recruiters into talent advisors 31:27 Keep what you kill: reinvesting time saved 35:23 Why AI headcount narratives are often misleading 37:49 Hiring for slope over snapshot 40:56 Building the TA workbench inside an agent harness 46:06 Using AI for traceability and coaching 48:12 Final advice on building AI fluency Tracy St.Dic: https://www.linkedin.com/in/tracy-stdic Zapier: zapier.com Using AI in Zapier’s hiring process: https://zapier.com/l/jobs/ai-at-zapier For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

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  Elevate Your AIQ

  Ep 134: Unpacking the Psychology Behind AI Success with Dr. Gleb

  Sep 4, 20261h 1m

  Bob is joined by Dr. Gleb Tsipursky, better known as Dr. Gleb, CEO and founder of Disaster Avoidance Experts and author of the new book “The Psychology of AI Adoption at Work: From Resistance to Results”. Drawing on over a hundred consulting projects and thousands of survey responses, Dr. Gleb explains why roughly 95 percent of AI pilots fail to show ROI, arguing the real obstacle is not the technology but three psychological profiles driving resistance: fear of job loss, threats to professional identity, and shame around quietly using AI in the shadows. They discuss how forced AI mandates can backfire into deliberately sloppy output, why untrained junior employees produce polished but poorly reasoned work, and the widening gap between how executives and everyday employees experience AI adoption. Dr. Gleb closes with practical fixes, from training people on tasks they hate first to having leaders model and reward AI usage openly. Keywords AI adoption, cognitive biases, decision science, psychology of AI adoption at work, change management, AI alarmists, pragmatic resistors, reluctant adopters, shadow AI use, AI slop, malicious compliance, psychographic profiles, identity threat, Office Whisperer, Disaster Avoidance Experts, MIT pilot study, Pew Research, leadership communication, AI training Takeaways 95 percent of AI pilots fail to show ROI because leaders treat a psychological challenge as a technical one Three psychographic profiles drive resistance: AI alarmists who fear job loss, pragmatic resistors who feel identity threat, and reluctant adopters who hide shameful shadow AI use Forced AI mandates can trigger malicious compliance, where resistant employees deliberately produce sloppy output to prove the tool does not work Untrained junior employees produce polished looking but poorly reasoned AI output, widening a generational skills gap Executives and rank and file employees experience AI adoption very differently, a split reality that hides the fear driving resistance Leaders reduce resistance by modeling their own AI usage publicly and rewarding employees who share new use cases Quotes It's not the technology that's a challenge. It's psychology. The technology is great. But the social stigma is high. You go slow to go fast. The leaders need to model AI usage. They need to talk about it. The crucial thing is leaders know that most people aren't engaged in their work. Chapters 00:03 Welcome and introductions 00:54 Dr. Gleb's background and the new book 07:00 Why 95 percent of AI pilots fail to show ROI 08:58 The real barrier is psychology, and the three resistance profiles 12:57 A real world story of shadow AI use and hidden shame 18:30 AI slop, malicious compliance, and untrained junior employees 27:37 The split reality between executives and employees 31:48 Reaching the AI alarmists and pragmatic resistors 38:47 Reaching the reluctant adopters through modeling and reward 52:01 Workshops, the DIY approach, and closing thoughts Dr. Gleb: https://www.linkedin.com/in/dr-gleb-tsipursky Disaster Avoidance Experts: http://disasteravoidanceexperts.com/ The Psychology of AI Adoption at Work: https://a.co/d/0cdkVi76 For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

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  Elevate Your AIQ

  Ep 133: Empowering Communities and Unlocking Self-Awareness with Anne Descalzo and Rachel Zillner

  Aug 28, 202655 min

  Bob sits down with Anne Descalzo and Rachel Zillner, co-founders of The RADZ Group, to trace their path from banking colleagues to serial entrepreneurs building a diverse portfolio of companies. Anne and Rachel share what it felt like to step back from the CEO seat at Clutch, the company they built from scratch, and how they grew a venture fund that invests in historically underserved founders. The conversation turns to LQ: Listening Intelligence, their behavioral AI platform built on cognitive science, and how it helps people uncover blind spots and communicate more effectively at work and at home. They also discuss how AI shows up across their portfolio and why they want more founders to share their stories. Keywords The RADZ Group, Anne Descalzo, Rachel Zillner, Clutch, Minerva Fund, LQ Listening Intelligence, behavioral AI, cognitive listening assessment, venture capital, underserved founders, CEO transition, self-awareness, communication, coaching, Rancho Cordova, AI ecosystem, candidate fraud, cybersecurity, workforce development Takeaways Anne and Rachel built Clutch together before growing it into The RADZ Group, a portfolio spanning government consulting, co-working, venture capital, marketing, and technology. Stepping back from a CEO role you built from scratch can bring genuine grief, even alongside pride and trust in new leadership. Their Minerva venture fund intentionally invests in historically underserved founders, with most portfolio companies female founded or led by a founder of color. LQ: Listening Intelligence draws on 15 years of cognitive science research to help people understand their own listening habits and adapt how they communicate. Behavioral AI built on that research can prep people for difficult conversations and reframe misunderstood behaviors, like mistaking reflective listening for indecisiveness. New AI risks are emerging too, including candidate fraud and cybersecurity threats tied to remote work. Anne and Rachel see in-person community as essential to how their region and portfolio companies keep pace with AI. They're on a mission to help more founders and leaders feel comfortable sharing their stories instead of staying under the radar. Quotes We think of projects like Play-Doh and everything has, you know, like a new shape that it can take. I came downstairs, very dramatically draped myself across to Anne's desk and just, if I could ever leave this place, would you go with me? And I now call that my proposal. Grief is associated a lot of times with death, but grief can also show up with transition and change. We have 15 years of scientific research. It's the only scientifically backed cognitive listening assessment in the world. We decided to start a venture capital fund to support other folks who don't always get the type of lending or support that they need. Imagine what could happen in the workplace when folks show up with that understanding. Chapters 00:02 Welcome and introductions 00:56 Meet Anne and Rachel 02:54 From banking colleagues to co-founders 04:15 The Clutch origin story 05:38 Building The RADZ Group portfolio 10:04 Stepping back as CEO and navigating grief 15:03 Introducing LQ Listening Intelligence 19:51 Behavioral AI for difficult conversations 22:34 Bringing the tool into everyday work 26:08 Uncovering hidden biases and rethinking labels 35:02 The future of listening as a standardized skill 37:15 Portable assessments and coaching applications 41:21 AI across the portfolio and the Rancho Cordova ecosystem 44:53 AI risks including candidate fraud and cybersecurity 48:16 What's next and encouraging founders to share their story Anne Descalzo: https://www.linkedin.com/in/anne-descalzo Rachel Zillner: https://www.linkedin.com/in/rachel-zillner The RADZ Group: https://www.theradzgroup.com/ For AI readiness advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

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