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  • Ep 131: Scaling Human-Centric AI in Government and Higher Ed with James Regan

    Ep 131: Scaling Human-Centric AI in Government and Higher Ed with James Regan
    2026/08/14
    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
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    53 分
  • Ep 130: Charting Career Reinvention and Prioritizing Responsible AI with Erika Oliver

    Ep 130: Charting Career Reinvention and Prioritizing Responsible AI with Erika Oliver
    2026/08/07
    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
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    1 時間 5 分
  • Ep 129: Modeling Transparency and Earning Trust in Recruiting with Gerry Crispin

    Ep 129: Modeling Transparency and Earning Trust in Recruiting with Gerry Crispin
    2026/07/31
    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
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    53 分
  • Ep 128: Owning Your AI and Capitalizing on Proprietary Data with Andrew Brooks

    Ep 128: Owning Your AI and Capitalizing on Proprietary Data with Andrew Brooks
    2026/07/24
    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
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    1 時間
  • Ep 127: Restoring Trust by Advancing Human-Positive AI with KVJ

    Ep 127: Restoring Trust by Advancing Human-Positive AI with KVJ
    2026/07/17
    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
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    59 分
  • Ep 126: Aiming AI at Human Bias and True Potential to Succeed with Trent Cotton

    Ep 126: Aiming AI at Human Bias and True Potential to Succeed with Trent Cotton
    2026/07/10
    Bob catches up with Trent Cotton, Head of Talent Insights and Analyst Relations at iCIMS, for a data-grounded look at why hiring feels so broken right now. Drawing on iCIMS workforce data, Trent unpacks a widening gap between job openings and actual hires, the rise of "job hugging," and application volumes falling below last year. The conversation digs into the real culprit behind entry-level frustration: a decades-old habit of confusing years of experience with actual skill, which AI is now exposing and scaling rather than causing. Trent makes the case for blowing up the traditional job ad in favor of a transparent scorecard, and for using AI to surface hidden bias and predict success rather than just automate the old process. They close on an optimistic note about Gen Z teaching themselves AI skills and why it may finally be time to retire the resume. Keywords talent acquisition, skills-based hiring, experience versus skills, job hugging, iCIMS workforce report, three-line report, entry-level hiring, Gen Z, early career, AI in hiring, recruiting bias, responsible AI, AI interviewer, job scorecard, job description, AI sourcing, quality of hire, retention, workforce data, future of work, Trent Cotton, Bob Pulver, Elevate Your AIQ Takeaways Job openings are rising faster than hires while application volume dips below last year, pointing to job hugging and recruiting teams stretched past their limits The "experience" bar is often a poor proxy for skill, a problem that predates AI by decades Skills-based hiring only works if organizations stop assuming years of experience are directly proportional to ability The job ad should be rebuilt as a transparent scorecard that candidates see going in and that drives consistent scoring across every interviewer AI does not create hiring bias so much as expose and scale the bias already there, and it can also help detect and coach against it (recency bias, manager patterns, and more) AI sourcing can pressure-test unrealistic requirements before a role is ever posted, turning recruiters into advisors rather than order-takers Gen Z is teaching itself AI skills and taking ownership of continuous learning, making it an overlooked and ready talent pool Fixing retention starts in the hiring process, by confirming candidates are not just qualified but genuinely want the role Quotes "We've been looking at experience, assuming that skills are directly proportional to the number of years of experience." "You can be working for 10 years at something and still suck at it." "The only thing that's different with AI is it's gonna find them, expose them, and scale them." "You just don't know until you give people a chance." "The resume needs to be retired. It's well past its retirement age." Chapters 00:02 Welcome and reconnecting 01:29 Trent's non-linear path from banking to HR 03:46 The unicorn role and the talent insights program 05:26 A new book and five mindsets for HR 06:40 What the market data reveals about hiring 08:53 Job hugging and a cautious candidate market 10:18 The experience trap and five years of LLM experience 14:01 Gen Z and the mid-level experience expectation 16:24 Skills versus experience and the self-taught coder 21:25 Blowing up the job ad and building a scorecard 29:17 The bias conversation AI is not having 36:26 A balanced narrative and smarter sourcing 44:43 Gen Z teaching themselves and the education gap 52:07 Retiring the resume and closing advice Trent Cotton: trentcotton.com iCIMS: icims.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
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    58 分
  • Ep 125: Democratizing Coaching and Strengthening Human Agency with Diane Weaver

    Ep 125: Democratizing Coaching and Strengthening Human Agency with Diane Weaver
    2026/07/03
    Bob is joined by Diane Weaver, co-founder and COO of Baryons, who brings a career defined by translation — across languages, disciplines, and roles — to what she describes as the most important problem she has ever worked on: human flourishing in the age of AI. Drawing on her background in EdTech, linguistics, and startup leadership, including the founding and acquisition of CourseTune, Diane shares how a post-exit identity crisis and the release of ChatGPT converged to spark the idea for Baryons. The platform is a voice-based AI companion designed to support mental wealth, resilience, and human agency through four modes: daily check-in, checkout, thinking partner, and flourishing partner. Diane and Bob explore the science behind the product, the organizational dysfunction it is built to address, and why Baryons was designed from day one to get people off AI and back into meaningful connection with other human beings. Keywords Baryons, human flourishing, mental wealth, human agency, resilience, voice AI, executive coaching, organizational health, edtech, CourseTune, systems thinking, neuroplasticity, burnout, resonance report, team dynamics, responsible AI, technology stewardship, Diane Weaver Takeaways Baryons is a voice-based AI companion that supports individual and organizational health through four modes: check-in, checkout, thinking partner, and flourishing partner The platform democratizes access to a daily practice long associated with high performers and executive coaching, making it available to every employee at $20 a month Baryons uses a patent-pending approach to memory, allowing it to surface patterns and prior conversations in ways that build continuity and accountability over time Weekly resonance reports give individuals and teams insight into energy levels, recurring themes, and early indicators of burnout — without exposing individual conversations The product is built on six well-researched domains of organizational health: coordination, shared reality, early risk visibility, decision quality, engagement, and learning velocity Diane frames the current moment not as a technology problem but as a human one, and argues that organizations fixated on productivity metrics are missing the signals that actually predict team resilience and long-term performance Baryons is intentionally designed to be non-addictive and non-affirming — it is built to help users identify root causes and reconnect with human beings, not keep them talking to an AI Quotes "I really want to be working with people who want to be doing something that was impossible to do before." "We talk about ourselves as being the first AI that is truly built and designed to get people off of AI and back connecting with human beings in the real world." "The interface is more of your inner world than anything else." "It doesn't matter that an individual resonance — or even a team — is always trending up. When everything's always trending up, you know as a leader they've gamed the system." "Those six functions of the organization have to be repaired — or they may survive all of this tech disruption and still be dysfunctional." Chapters 00:02 Welcome and introductions 00:46 Diane's background: from the family farm to edtech and entrepreneurship 10:11 The paparazzi story: Pat Weaver, the Today Show, and a legacy of democratizing technology 12:41 The genesis of Baryons and the post-ChatGPT moment 15:33 Human agency as the core design principle 18:26 How Baryons works: voice-first design and the check-in mode 21:48 Shifting from technology users to technology stewards 23:38 The checkout mode: cognitive offloading and ending the workday with clarity 26:01 The thinking partner and flourishing partner modes 29:48 Democratizing executive coaching and the value of a non-judgmental AI 36:47 Why voice is the right interface: psychological safety and trust 41:15 A user story: Baryons as a neutral mediator in a fractured friendship 43:29 Mental wealth vs. mental health: resilience as a daily practice 47:34 Resonance reports: individual and team insights, burnout signals, and the limits of productivity metrics 52:00 Choosing the right partners: ethical AI, organizational dysfunction, and the six domains of health 59:51 What's ahead: Baryons.com, community brain health initiatives, and keeping humans at the center Diane Weaver: https://www.linkedin.com/in/weaver-diane Baryons: https://baryons.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
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    1 時間 2 分
  • Ep 61: Assessing AI Literacy, Readiness, and Maturity with Eryn Peters and Iwo Szapar

    Ep 61: Assessing AI Literacy, Readiness, and Maturity with Eryn Peters and Iwo Szapar
    2026/07/01
    Bob Pulver catches up with Erin Peters and Iwo Szapar to explore the evolving landscape of AI literacy and their AI Maturity Index (AIMI). They discuss the importance of understanding how AI is being utilized in the workplace, the development of AIMI to benchmark AI readiness, and the STEP framework for implementing AI strategies. The conversation hits on the distinction between automation and augmentation, challenges orgs face in measuring productivity, and the need for a more nuanced understanding of AI's value proposition. Bob and his guests discuss the multifaceted aspects of AI adoption, how to measure progress, how to gauge maturity levels, and the importance of benchmarking. They explore the evolving landscape of AI skills in hiring, cultural shifts towards AI integration, and the necessity of responsible innovation. The dialogue also touches on the governance and ethical considerations surrounding AI, as well as global perspectives on its implementation, particularly in regions like Saudi Arabia. Keywords AI literacy, AI maturity index, future of work, automation, augmentation, productivity, change management, digital transformation, workforce development, AI strategy, AI adoption, organizational maturity, competitive benchmarking, AI skills, hiring trends, cultural shifts, responsible innovation, AI governance, global AI perspectives Takeaways AI literacy is crucial for the future of work. The AI maturity index helps organizations benchmark their AI readiness. The STEP framework simplifies AI implementation processes. Many organizations struggle with AI implementation despite having strategies. AI can enhance productivity and work-life balance. Understanding the real value of AI goes beyond cost savings. Personalized approaches to AI implementation are essential. The landscape of AI is rapidly evolving, requiring continuous learning. Measuring AI adoption success requires real data, not just anecdotes. Departments within organizations may have varying maturity levels in AI adoption. AI skills are becoming essential in hiring practices across industries. Cultural shifts are influencing how organizations embrace AI technology. Responsible innovation is crucial for leveraging AI effectively. AI governance must balance control with worker empowerment. Global perspectives on AI adoption reveal significant regional differences. Organizations need to adapt to the rapid pace of AI advancements. Sound Bites "AI is going to steal your job." "We help individuals, teams and organizations." "Democratize access to insights." "80% of AI implementation projects are failing." "AI can really help fix a lot of challenges." "It's about making my life easier." "We need to start looking at real value." "This is what I'm doing right now." "We can go more in depth, more personalized." "We're all tech enabled in different ways." "This is a balancing act of guided empowerment." Chapters 00:00 Introduction to AI Literacy and Maturity Index 03:49 Understanding the AI Maturity Index 11:44 The STEP Framework for AI Implementation 18:43 Navigating Automation vs. Augmentation 23:23 Measuring AI Value Beyond Cost Savings 25:55 Measuring Success in AI Adoption 30:23 Understanding Organizational Maturity in AI 31:21 The Competitive Edge of AI Benchmarking 32:58 The Future of AI Skills in Hiring 37:12 Cultural Shifts in AI Adoption 40:37 Responsible Innovation in AI 46:05 Navigating AI Governance and Ethics 50:00 Global Perspectives on AI Implementation Eryn Peters: https://www.linkedin.com/in/erynpeters Iwo Szapar: https://www.iwoszapar.com/ For advisory work and marketing inquiries: Bob Pulver: https://linkedin.com/in/bobpulver Elevate Your AIQ: https://elevateyouraiq.com Thanks to Warden AI (https://warden-ai.com) for their sponsorship and support of the show! Warden is an AI assurance platform for HR technology to demonstrate AI-powered solutions are fair, compliant and trustworthy.
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    55 分