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.

  1. 1 day ago

    Unpacking the Psychology Behind AI Success with Dr. Gleb

    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

    Unpacking the Psychology Behind AI Success with Dr. Gleb
  2. 28 Aug

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

    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

    Empowering Communities and Unlocking Self-Awareness with Anne Descalzo and Rachel Zillner
  3. 21 Aug

    Untangling AI Readiness and Prioritizing Workforce Data with Olivier Vidal

    Bob sits down with Olivier Vidal, founder of Sightline and a longtime HR tech product leader, for an overdue conversation on AI readiness. They explore why enterprise ambitions for AI so often outpace the underlying data and organizational maturity needed to support them, and how the workforce dataset is becoming an increasingly strategic asset. The conversation turns to how AI evaluation differs from traditional software testing, the risks of vibe coding sensitive HR processes, and the many, sometimes conflicting, definitions of AI readiness circulating in the industry. Bob and Olivier also dig into explainability, using analogies from mapping apps and self-driving cars, and close with a candid look at how much of the substantive decision-making has already shifted from humans to AI systems. Keywords AI readiness, workforce data, HR tech, Talent Intelligence Collective, Sightline, data maturity, AI evaluation, vibe coding, responsible AI, explainability, agentic AI, WPP, Adecco, human-AI teams Takeaways Enterprise AI ambitions routinely outpace the data and organizational readiness needed to support them, a gap Olivier sees at companies of every size Workforce data is poised to become a top-tier strategic asset as agentic AI needs much higher-fidelity information to orchestrate human and AI work Traditional HRIS systems and fragmented tool stacks miss the unstructured, contextual data AI systems actually need AI evaluation is a distinct discipline from traditional software QA, requiring specialized expertise to stress-test models and guardrails Olivier cautions against vibe coding AI solutions for sensitive HR use cases without proper evaluation and governance AI readiness spans individual skills, technical model controls, and organizational information flows, and conflating them creates confusion As AI takes on more decision-making in workforce tools, human oversight risks becoming a rubber stamp unless systems are genuinely explainable Real transformation requires redesigning workflows and roles around AI, not just layering AI onto existing jobs Quotes “In an awful lot of the projects I've been involved in, the hopes and dreams of senior management have been miles ahead of the actual preparedness of a business to feed a given system with the information it needs to make decisions” “If you follow the logic through to its sort of maturity, ultimately, the company's own data set is the product” “I'm really cautious about vibe coding anything frankly that touches sensitive data. It's a different club, a different mindset. I'm not in it” “There are a lot of people building ‘agents’ for things that could just be basically automated rules” “We're beyond the point where the humans are actually making the substance of the decision. They are just acting as a fail safe on have we done anything monumentally unfair or monumentally stupid” “Sightline is a new AI readiness practice for workforce products, we look at all of the client side data and knowledge that feeds systems and makes them work” Chapters 00:02 Welcome and introductions 01:15 Olivier's HR tech backstory 03:40 Readiness gaps across big and small companies 06:19 Trust and the rising value of workforce data 12:18 Human-AI teams, data quality, and tool sprawl 16:10 Talent intelligence and the data as product 22:18 AI evaluation, vibe coding, and where the caution lies 29:22 Untangling AI literacy, fluency, and readiness 33:14 Defining organizational AI readiness 38:53 Accountability, explainability, and the Google Maps analogy 49:10 WPP's value chain and disrupting your own role 52:46 Fear of change, adoption, and Sightline's parting words Olivier Vidal: https://linkedin.com/in/ojvidal Sightline: sightline-ai.co 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

    Untangling AI Readiness and Prioritizing Workforce Data with Olivier Vidal
  4. 14 Aug

    Scaling Human-Centric AI in Government and Higher Ed with James Regan

    James Regan, CEO of Clutch, joins Bob to unpack what he learned leading some of the earliest generative AI deployments inside California state government under Governor Newsom's 2023 executive order. James traces his path from public health in Health and Human Services to Deputy Secretary for Workforce Development, and explains how procurement and change management had to be rebuilt to keep pace with AI. He and Bob discuss why reducing employee fear of AI starts with human centered design, and why the real opportunity in workforce AI is skills matching tools built for job seekers, not just recruiters. They also cover California's Career Passport initiative, Clutch's change management method built on the human trauma curve, and how universities are rethinking AI literacy for the future workforce. Keywords James Regan, Clutch, California state government, Governor Newsom, generative AI, workforce development, Google Public Sector, AI governance, procurement policy, change management, human centered design, human trauma curve, skills based hiring, skills matching, career mapping, veterans, Career Passport, AI literacy, higher education, AI readiness, job displacement fear Takeaways: Early generative AI pilots in California state government spanned transportation, health and human services, and tax, proving out real production use cases under Governor Newsom's 2023 executive order. Sustainable AI adoption in government required rebuilding procurement, since traditional buy once, freeze code IT purchasing does not fit generative AI's constant evolution. Human centered design and consistent, repeated communication, not just tooling, are what actually reduce employee fear of AI driven job displacement. The bigger opportunity in workforce AI is not recruiter facing tools, it is skills matching tools that help job seekers, including veterans, translate existing skills into new job qualifications. Skills based hiring is gaining ground as employers move away from defaulting to a four year degree, especially with AI driving demand for skills learned through certifications. California's Career Passport initiative aims to create a portable, verified record so job seekers do not have to repeatedly prove the same credentials. Clutch is launching a change management method built on the cognitive science of the human trauma curve, designed to quantify and reduce individual resistance to workplace AI rollouts. Quotes: "One of the things that drove our philosophy was creating a safe space to learn by doing." "It's not something happening to them. It's something that is happening with them and with their input and support." "The post and pray method does not work. It does not work." "I think one of the biggest fears that we're hearing in sentiment across the state among students is not knowing which degree program or which education track to pick." "A lot of AI tools are being deployed in a way that reinforces the fear and doubt of its effectiveness. We're here to shatter that problem." Chapters: 00:02 Welcome and introductions 00:42 James's path from public health to California state government 02:34 Early generative AI pilots launched under Governor Newsom 06:04 Procurement, governance, and vendor partnerships in early AI rollouts 10:32 AI readiness, job displacement fears, and human centered design 19:36 Rapid AI deployment and balancing stakeholders in the process 23:12 Skills matching and skills based hiring for job seekers 35:41 California's Career Passport and verified learning records 40:17 Clutch's new change management method built on the human trauma curve 46:50 University partnerships and the future workforce 51:00 Closing thoughts and where to find Clutch James Regan: https://www.linkedin.com/in/james-regan-jr Clutch: https://www.clutchgov.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

    Scaling Human-Centric AI in Government and Higher Ed with James Regan
  5. 7 Aug

    Charting Career Reinvention and Prioritizing Responsible AI with Erika Oliver

    Bob sits down with Erika Oliver, Founder and Managing Director of NewtonHaus and Executive Analyst at Aptitude Research, for a wide ranging look at where AI is really landing in HR and the workforce. Erika shares her non-linear path through executive search and coaching, an unexpected pivot into labor market intelligence, and a moment that reset her priorities and sharpened her focus on the human side of work. The two dig into the shift from the year of the pilot to hard questions about ROI, why AI readiness now includes security and guardrails, the difference between responsible and human-centric AI, and the build versus buy pressure facing HR tech. It is equal parts career wisdom and market analysis, with a part two already in the works. Keywords AI readiness, responsible AI, human-centric AI, AI pilot, AI ROI, HR tech, talent acquisition, talent intelligence, workforce analytics, executive search, executive coaching, career pivot, build versus buy, agentic AI, security, guardrails, candidate experience, veterans hiring, neurodiversity, transformation, IBM Watson, NewtonHaus, Aptitude Research, Erika Oliver, Bob Pulver, Elevate Your AIQ Takeaways The market is shifting from the year of the pilot to a harder reckoning over ROI and where AI truly delivers value. AI readiness now goes beyond willingness to adopt; security, guardrails, and responsible deployment are central to the conversation. Responsible AI and human-centric AI overlap but are not the same, and the onus for human-centric deployment sits largely with buyers, not just vendors. Responsibility starts with the individual, using AI where you should rather than wherever you can, not waiting for a corporate framework or legislation. Build versus buy is a real pressure point for HR tech, and building responsible, enterprise grade solutions is far harder than it looks. Career reinvention is possible amid fear and uncertainty, and the right opportunity is often the one you least expect. Quotes "Sometimes the opportunity that is for you is the one that you least expect, the one that you don't think you're qualified for." "Regardless of the fear, regardless of the unknown, there is a path forward. You just have to be dedicated to seeing that through and what that means for you." "Don't let somebody else tell you solely how to be responsible." "As someone who's come from the vendor side, it's as much the responsibility of the buyer and the enterprise." "The load is greater if it's done responsibly than I think a lot of boards and a lot of C level folks realize." "If you don't invest in people, then it doesn't matter how much you spend on tokens." (Bob) "Hold yourself accountable for using AI where you should, not wherever you can." (Bob) Chapters 00:02 Welcome and introductions 01:08 Erika's winding path through executive search and coaching 06:08 An unexpected pivot into AI powered labor market intelligence 12:01 A health scare that reset her priorities 16:13 Building a portfolio of coaching, advisory, and analyst work 20:23 The year of the pilot and the push to prove ROI 27:57 Readiness, responsible AI, and human centricity 30:08 When agentic AI goes rogue and security takes center stage 32:33 Being responsible by design and accountable builders 38:11 The three pillars and why responsibility starts with us 42:37 Transformation, Watson, and adapting to constant change 44:49 Solving for candidates, veterans, and neurodiversity 54:09 The build versus buy pressure facing HR tech 1:00:13 Responsible AI in the build versus buy calculus 1:04:09 Closing thoughts on pace, people, and part two Erika Oliver: https://www.linkedin.com/in/eoliver Newton Haus: newton-haus.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

    Charting Career Reinvention and Prioritizing Responsible AI with Erika Oliver
  6. 31 Jul

    Modeling Transparency and Earning Trust in Recruiting with Gerry Crispin

    Gerry Crispin, founder of CareerXroads and a five-decade veteran of the talent industry, joins Bob to trace recruiting's evolution from paper resumes and fax machines to today's AI-driven hiring landscape. Gerry reflects on the origins of CareerXroads as a trusted peer community built on open sharing rather than competition, and explains why he sees knowledge hoarding as a losing strategy for the industry. The conversation turns to one of recruiting's most persistent failures, candidate ghosting, and how AI agents could actually make the process fairer and more consistent than overworked human recruiters manage today. Gerry and Bob close by imagining a future of verified digital twins that let candidates and employers build trust on their own terms, and why there is no going back to a pre-technology hiring era, only forward toward something more human-centric. Keywords Gerry Crispin, CareerXroads, talent acquisition, recruiting technology, candidate experience, candidate ghosting, applicant tracking systems, AI agents, AI screening, digital twins, human-centric AI, social capital, responsible AI, candidate feedback, trust and transparency Takeaways Gerry Crispin's five-decade recruiting career and 30 years building CareerXroads trace the industry from paper resumes and fax machines to AI-driven hiring. Real community differs from a network: people who call you back, not just first-degree LinkedIn connections. Knowledge sharing creates a bigger pie for everyone; zero-sum thinking about proprietary recruiting practices holds the industry back. Candidate ghosting remains rampant, and Gerry estimates more than half of US employers intentionally leave applicants without a response, despite ATS tools that could prevent it. AI agents could bring more consistency, and even more humanity, to candidate communication than an overworked recruiter handling hundreds of applicants across dozens of open roles. The best recruiters already give rejected candidates honest, constructive feedback quietly, without their employer's blessing. The goal is to make that the norm. Gerry envisions a future of AI-verified digital twins that let candidates and employers exchange trustworthy information on their own terms, similar to how actors fought to protect their likeness. Going backward to paper resumes and in-person-only interviews isn't realistic. The real work is reimagining recruiting for every stakeholder as trust-building technology matures. Quotes: "I believe and I've always believed that the expertise is in learning." "A lot of people think in terms of zero-sum games: the more I share, the less of the pie I'm going to have. As opposed to the bigger pie we both create for all of us." "A candidate says, 'I want a human to talk to.' It's not a choice between a human or a non-human. It's a choice between a non-human or nothing." "There's an ability with the technology we have today to tell candidates we're not going forward with them... there's just no excuse not to do that." "The question is whether we're doing the wrong things with new technology, or are we reimagining how we could do things more effectively." Chapters: 00:03 Welcome and introduction of Gerry Crispin 01:10 CareerXroads' 30 years and owning your career 05:36 Fax machines, ATS pain points, and the internet's arrival 10:08 Building CareerXroads as a trusted peer community 12:23 Trust, community, and IBM's social computing guidelines 17:52 Working out loud, social capital, and the moving target of expertise 24:26 Ghosting, missing feedback, and a more humane hiring agent 42:02 Algorithms, consistency, and human centricity 46:28 Digital twins, boundaries, and a human-in-the-loop future Gerry Crispin: https://www.linkedin.com/in/gerrycrispin CareerXroads: https://community.cxr.works/home 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

    Modeling Transparency and Earning Trust in Recruiting with Gerry Crispin
  7. 24 Jul

    Owning Your AI and Capitalizing on Proprietary Data with Andrew Brooks

    Andrew Brooks, CEO and Founder of Contextual.io, joins Bob to trace a career that runs from early-internet consulting through three exits (Seven Space to Sun Microsystems, a marketing company to ReachLocal, and SmartThings to Samsung) before landing on AI. Andrew explains Contextual's "own your AI" philosophy, why businesses should design, build, and operate their own systems rather than lock into a single model provider, and how real transformation comes from deepening a company's data, process, or relationship moats rather than chasing cost takeout alone. They dig into real client stories, from a commercial refrigeration estimator's tacit knowledge to a vacation rental company that discovered unexpected revenue recovery through AI-audited work orders. The conversation closes on what's shifting for engineering talent, why "human in the loop" needs more precision, and why waiting for the perfect model is a losing strategy. Keywords Contextual, Andrew Brooks, own your AI, agentic AI, AI orchestration, mid-market businesses, AI moats, model selection, Digital Greg, tacit knowledge, automation vs facilitation, human in the loop, agent sprawl, AI governance, private equity, Southfield Capital, system design, engineering talent, responsible AI by design, SmartThings, Seven Space, MCP, rational optimism Takeaways "Own your AI": build a system-agnostic layer instead of locking into one model or provider Durable AI investments deepen an existing moat, whether data, tacit knowledge, or relationships, not just cut costs Automation builds trust and adoption, but resist treating AI as a hammer for every problem Well-designed systems surface second and third order value nobody planned for Talent is shifting toward system designers who can spot edge cases and challenge AI outputs Waiting for a "perfect" model is a losing strategy given the pace of change Quotes "The phrase we use is own your AI. Do not become too embedded in a single provider or a single model, because you need to be able to react to what's happening in the space." "Not everything's an AI problem. Some things are process, and some things are just workflow." "You can't wait for the perfect model. The models are revving every ten, fifteen days. The pace of change is just too fast. You need to get into the river." "AI can be confidently wrong, and very confidently wrong. You've got to be able to see that and flag it." "I'm in the rational optimist camp here. AI might change jobs, but we've been changing jobs for many, many years." Chapters 00:01 Welcome and introducing Andrew Brooks 00:35 From Accenture to entrepreneurship: Seven Space, Reach Local, and SmartThings 03:45 Landing on AI and founding Contextual 04:41 Design, build, operate: how Contextual works with clients 08:33 Choosing the right model without over-committing to one provider 10:04 Beyond chatbots: agentic systems and finding your AI moat 12:36 Automation as an on-ramp to bigger AI thinking, and avoiding the shiny-hammer trap 17:58 Systems thinking, from Smart Things to agentic infrastructure 21:27 Responsible design, client collaboration, and unexpected value from clean data 28:19 Bad data, bad processes, and why waiting for the perfect model is a mistake 30:00 Where humans stay central and what "team superpowers" means 35:51 Vacation rental case study: audits, revenue recovery, and upsell insight 41:50 Getting acquired by a PE firm and what it means for AI adoption 45:20 Tool sprawl, governance, and rethinking "human in the loop" 51:45 Engineering talent, adaptability, and the Stripe MCP lesson in trust Andrew Brooks: https://www.linkedin.com/in/andrewcarrollbrooks Contextual.io 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

    Owning Your AI and Capitalizing on Proprietary Data with Andrew Brooks
  8. 17 Jul

    Restoring Trust by Advancing Human-Positive AI with KVJ

    Katherine von Jan (KVJ), CEO and Co-founder of Tough Day and a longtime innovation leader across Lotus Development, IBM, Salesforce, and multiple startups, joins Bob to trace a career built on one consistent thread: putting culture and human potential at the center of technology. The conversation covers the perils of workforce surveillance AI, why "human in the loop" has become a nearly meaningless phrase without real definition, and how KVJ's Human Positive Company framework gives organizations a way to evaluate whether their AI and culture choices are actually earning trust. They dig into the ethical review process that killed a risky Salesforce AI project (and the better one that replaced it), how KVJ's earlier startup RadMatter tackled bias against non-Ivy League candidates, and what her team learned about great management while building the AI behind Tough Day. It's a wide-ranging, practitioner-level conversation about responsible innovation, moral leadership, and what it actually takes to build AI people can trust. Keywords: human-centric AI, responsible AI, AI governance, workforce surveillance, human in the loop, AI ethics, Human Positive Company framework, Tough Day, Tuffy, RadMatter, Salesforce, IBM, Lotus Development, Irene Greif, talent acquisition, hiring bias, quality of hire, employee trust, ethical review, red teaming, collective intelligence, workplace culture, moral leadership, AI slop, skills-based hiring, retention Takeaways: KVJ's path from anthropology and Lotus Development (working for Irene Greif) through IBM, Salesforce, and now Tough Day traces one consistent thread: technology in service of culture and human potential "Human in the loop" is losing meaning as a governance concept; every stage of a workflow, like a recruiting funnel, is a decision point that either includes or excludes real human judgment Workforce surveillance AI, tools that flag "risk" signals across email, Slack, and HR systems, is a dangerous use case that erodes trust rather than building it Responsible innovation requires research and ethical review before deployment, not just fast iteration; Salesforce's own attrition-prediction AI backfired until it was redesigned into a re-recruiting tool instead KVJ's Human Positive Company framework evaluates organizations across three pillars: workforce ingenuity, positive-sum prosperity, and the ethical and humane use of AI RadMatter, her earlier startup, aimed to give overlooked and non-Ivy-League students visibility with employers, a problem that still shapes bias in AI-driven hiring today Building AI that reflects an organization's values starts with defining those values clearly and creating a real process, not just a poster on the wall, for employees to raise concerns Great management often looks like curiosity, asking more questions before offering answers, a pattern KVJ observed directly while researching how to train Tough Day's AI Quotes: "A coalition is designed to go solve something." - KVJ "You don't just go build the app. You build the research first." - KVJ "A lot of organizations have values written on the wall and that's as far as it goes." - KVJ "We're getting AI slop, and we're getting process slop, and we're getting application slop." - KVJ "Every employee is responsible for understanding, what am I complicit in?" - KVJ "Human in the loop is almost meaningless at this point. What is the loop? And where is the human in said loop?" - Bob Chapters: 00:01 Welcome and introductions 01:00 KVJ's path into tech: anthropology, Lotus Development, Irene Greif, and IBM 08:09 The strange LinkedIn deactivation and the leap to Salesforce 12:26 Comparing culture and tools across IBM, Salesforce, and beyond 15:13 Early social network analysis and today's AI parallels 18:32 Where to draw the line: what AI should do, not just what it can 21:27 Workforce surveillance AI and the danger of thinning out the workforce 25:47 Responsible innovation and human-positive AI 29:34 Inside the Human Positive Company framework 33:32 Measuring what matters: retention, morale, and moral leadership 37:05 Rethinking human in the loop across the recruiting funnel 38:26 RadMatter and surfacing overlooked talent 43:26 Building governance: ethics committees and guardrails 47:06 Training Tough Day's AI on values, culture, and what research reveals about great management 57:20 Closing thoughts and a call to action KVJ: https://www.linkedin.com/in/kvonjan Tough.Day: https://tough.day For advisory work and marketing inquiries: Bob Pulver:⁠⁠ ⁠https://linkedin.com/in/bobpulver⁠⁠⁠ Elevate Your AIQ:⁠⁠ ⁠https://elevateyouraiq.com⁠⁠⁠ Substack: ⁠https://elevateyouraiq.substack.com⁠

    Restoring Trust by Advancing Human-Positive AI with KVJ

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.

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