EP20: The K-Shaped Knowledge Economy: Why AI Fluency Is Splitting the Workforce

EP26: The Human Side of AI: Trust, Fear, and Why Change Management Must Change with Dr. Xenia Wade

What happens when employees walk into AI training already convinced the technology might replace them? Most organizations are treating AI adoption as a technology challenge. Dr. Xenia Wade believes that is exactly where leaders are getting it wrong. Drawing from her research background, enterprise transformation work, and recent move from Germany to Japan, Xenia explains why AI creates a level of fear and vulnerability that previous technology transformations never did. Employees are not just learning a new tool. Many are questioning their future, their identity, and the value of skills they spent years developing. In this conversation, we explore why psychological safety has become a prerequisite for AI adoption, why traditional change management is no longer enough, and why trust may be the most important capability leaders need to build right now. HIGHLIGHTS: * Why AI triggers fear in ways previous technology transformations never did * The connection between psychological safety and successful AI adoption * Why employees often arrive at training with strong opinions before learning begins * The difference between AI training and true AI education * How leaders can build trust by modeling vulnerability and uncertainty * Why honesty is more powerful than certainty during periods of transformation * The hidden danger of measuring AI success through token usage and adoption metrics alone * What "token maxing" reveals about flawed AI ROI measurement * Why traditional change management still matters, but is no longer enough * How organizations can create cultures where people feel safe experimenting with AI * The role of judgment, confidence, and human capability in an AI-enabled future GUEST: Dr. Xenia Wade is a transformation strategist, researcher, and advisor focused on the human side of AI adoption and organizational change. With a PhD in Human Resource Management, her research explored how employees learn from one another and how workplace dynamics influence behavior and performance. She later brought those insights into enterprise transformation work, helping organizations navigate large-scale digital change initiatives. Now based in Japan after relocating from Germany, Xenia combines academic research with practical transformation experience to help leaders understand the psychological, cultural, and human dimensions of AI adoption. Her work focuses on psychological safety, trust, leadership behavior, change management, and the future of human-AI collaboration. FOLLOW JASON AVERBOOK: Substack: https://substack.com/@jasonaverbook [https://substack.com/@jasonaverbook] X: https://x.com/jasonaverbook [https://x.com/jasonaverbook] LinkedIn: https://www.linkedin.com/in/jasonaverbook [https://www.linkedin.com/in/jasonaverbook] Instagram: https://www.instagram.com/jasonaverbook [https://www.instagram.com/jasonaverbook] YouTube: https://www.youtube.com/@nowtonextwithjasonaverbook [https://www.youtube.com/@nowtonextwithjasonaverbook] Facebook: https://facebook.com/jasonaverbook [https://facebook.com/jasonaverbook] FOLLOW XENIA WADE: LinkedIn:https://www.linkedin.com/in/xenia-wade/ [https://www.linkedin.com/in/xenia-wade/] Website: https://xeniawade.com/ [https://xeniawade.com/] Substack: https://xeniawade.substack.com/ [https://xeniawade.substack.com/] Free guide, 3 moves to get a stalled AI rollout moving: https://xeniawade.com/field-guide/ [https://xeniawade.com/field-guide/] (0:00) Introduction and Dr. Xenia Wade's background (2:35) The human side of change and technology (3:47) AI and human interaction (6:04) Psychological safety in the workplace (9:20) Creating a culture of safety and vulnerability (13:57) Human bottlenecks in technological adoption (17:37) Comparing AI adoption to past tech changes (20:52) External factors shaping employee perception of AI (24:08) Rebuilding trust in AI and institutions (26:11) Training AI versus building trust (28:07) Building psychological safety in organizations (30:23) Meaningful education for job security (32:31) Shifting focus from IT to people (34:32) Measuring ROI in AI projects (36:44) Psychological safety and trust in the workplace (38:53) Key takeaways for leaders (39:56) Optimism in the age of AI (42:37) Balancing benefits and downsides of AI (43:20) Connecting with Dr. Xenia Wade

EP25: The Trust Collapse: Why Your Workforce Has Stopped Believing Your AI Strategy

BCG dropped two studies that should be taped to the wall of every CHRO's office. One shows that adding AI "employees" to org charts is making human workers sloppier and more likely to blame the bot when things go wrong. The other — "AI brain fry" — shows that cognitive overload from managing AI tool sprawl is driving errors, burnout, and intent to quit. Meanwhile, 48% of Q1 tech layoffs were attributed to AI, Gen Z workers are listing AI skills they don't have on their résumés, and boards are demanding governance answers most executives cannot give yet. But the story underneath all of that — the one you won't find in any headline today — is a trust collapse. Workers don't believe what leaders are telling them about AI anymore. And that gap is now a credibility crisis. This episode is about all of it. HIGHLIGHTS: * Why BCG’s latest research found AI workers can reduce human accountability * The rise of “AI brain fry” and the hidden cost of tool sprawl * Why employees are increasingly disconnected from leadership AI narratives * The growing credibility crisis around augmentation vs replacement * How organizations are accidentally creating burnout through poor AI experience design * Why eliminating junior roles without redesigning development pathways creates long term risk * The dangerous rise of inflated AI skills data across the workforce * Why boards are asking governance questions most executive teams still cannot answer * The difference between deploying AI and redesigning work for humans HOST BIO: Jason Averbook has spent thirty years watching the gap between where organizations say they are with technology and where work is actually happening. He has a name for it. He has a framework for closing it. And he built Now to Next to do exactly that. Now to Next is the AI studio Jason co-founded with Jess Von Bank in 2026 — built on practitioner intelligence, original research, and the conviction that human transformation precedes digital transformation. Always has. Always will. Before Now to Next, Jason co-founded Leapgen, acquired by Mercer in 2023, where he led global HR transformation strategy and the firm's generative AI practice. Earlier he served as CEO of The Marcus Buckingham Company, co-founded Knowledge Infusion through its acquisition by Appirio, and held senior roles at PeopleSoft and Ceridian. He has advised hundreds of Fortune 1000 companies, authored two books on the future of HR and workforce technology, delivered more than 1000 keynote presentations globally, and teaches as an adjunct professor at universities worldwide. He is consistently recognized as one of the top three thought leaders globally on the future of work. FOLLOW JASON AVERBOOK: Substack: https://substack.com/@jasonaverbook [https://substack.com/@jasonaverbook] X: https://x.com/jasonaverbook [https://x.com/jasonaverbook] LinkedIn: https://www.linkedin.com/in/jasonaverbook [https://www.linkedin.com/in/jasonaverbook] Instagram: https://www.instagram.com/jasonaverbook [https://www.instagram.com/jasonaverbook] YouTube: https://www.youtube.com/@nowtonextwithjasonaverbook [https://www.youtube.com/@nowtonextwithjasonaverbook] Facebook: https://facebook.com/jasonaverbook [https://facebook.com/jasonaverbook] SOURCES CITED: * BCG / Fortune: "Adding AI 'employees' is backfiring" (May 28, 2026) * BCG / HBR: "AI brain fry" — 1,488 workers surveyed (March 2026) * Oliver Wyman CEO Survey: 43% of executives cutting junior roles, up from 17% (Q2 2026) * Fast Company: "Skills manifesting — workers citing skills they intend to learn" (May 2026) * Society for Corporate Governance / Nasdaq: "AI in the Boardroom" (May 2026) (0:00) Introduction and the importance of designing AI for humans (1:17) Trust crisis and AI's impact on worker-leader relationships (1:52) BCG study and AI agents as employees (3:12) Leaders' reactions and responsibility for AI onboarding (6:22) AI brain fry, cognitive overload, and experience design (10:44) AI's impact on tech layoffs and junior roles (17:00) AI governance and executive challenges (18:14) Trust collapse revisited and key takeaways (20:34) Summary and closing remarks

EP24: The Function Nobody Owned: HR, IT, and AI Finally in One Room with Tracey Franklin

What does it really take to integrate people, culture, and technology in a way that drives transformation, not just change? As organizations race to adopt AI and digital platforms, many are still treating technology and people as separate strategies. But what happens when those two become one system? In this conversation, I sat down with Tracey Franklin, Chief People and Digital Technology Officer at Moderna, to explore what it actually looks like to connect people and technology in practice, not just in theory. Tracey shares her experience scaling Moderna from 800 to nearly 6,000 employees during one of the most critical moments in modern healthcare, and how that growth required rethinking not just talent, but how work itself gets done. We talk about why integrating HR and digital technology is no longer optional, how AI is reshaping decision-making and operating models, and what leaders often miss when trying to modernize their organizations. This is a conversation about building organizations that are designed to evolve, where culture, capability, and technology are not competing priorities but deeply interconnected system HIGHLIGHTS: * Why separating people strategy and technology strategy is breaking organizations faster than AI is transforming them * What leaders misunderstand about scaling culture during hypergrowth moments like Moderna experienced * The real reason most digital transformations fail even when the technology works * What changes when HR and technology leadership sit under one vision instead of operating in silos * How AI is shifting not just productivity, but how decisions get made across the enterprise * The tension leaders must navigate between speed, innovation, and maintaining human connection GUEST: Tracey Franklin is Moderna’s Chief People and Digital Technology Officer, where she leads the integration of people, culture, and digital innovation to shape how the organization operates and evolves. Since joining Moderna in 2019 as Chief Human Resources Officer, she played a critical role in scaling the company from 800 to nearly 6,000 employees during the COVID-19 pandemic while helping build a culture recognized globally as a top employer by Science. In 2024, her role expanded to include Digital Technology, reflecting the growing importance of aligning human capability with technological advancement, particularly in the age of AI. Before Moderna, Tracey spent 15 years at Merck & Co., Inc., where she held multiple global leadership roles, including Vice President, HR Chief Talent and Strategy Officer. Her experience spans global talent strategy, organizational transformation, and HR leadership across the U.S., UK, and Switzerland. She holds a BA in Communication Arts and Sciences from Pennsylvania State University and an MA in Industrial and Organizational Psychology from Fairleigh Dickinson University. FOLLOW JASON AVERBOOK: Substack: https://substack.com/@jasonaverbook [https://substack.com/@jasonaverbook] X: https://x.com/jasonaverbook [https://x.com/jasonaverbook] LinkedIn: https://www.linkedin.com/in/jasonaverbook [https://www.linkedin.com/in/jasonaverbook] Instagram: https://www.instagram.com/jasonaverbook [https://www.instagram.com/jasonaverbook] YouTube: https://www.youtube.com/@nowtonextwithjasonaverbook [https://www.youtube.com/@nowtonextwithjasonaverbook] Facebook: https://facebook.com/jasonaverbook [https://facebook.com/jasonaverbook] FOLLOW TRACEY FRANKLIN: LinkedIn: https://www.linkedin.com/in/tracey-franklin-8b731b1/ [https://www.linkedin.com/in/tracey-franklin-8b731b1/] (0:00) Introduction (2:28) Moderna's growth and pandemic response (3:35) The "blank sheet of paper" approach in HR and digital roles (5:12) Combining HR and IT: Challenges, benefits, and rebuilding vs. incremental changes (10:03) Managing human and machine resources (12:20) AI's impact on HR roles and democratizing AI access (14:52) Upskilling HR for AI and evolving skill sets (19:02) The future of HR: AI, human interaction, and rapid advancements (25:24) Vibe coding: Viability, practicality, and applications at Moderna (27:32) Importance of data in AI integration (32:22) K-shaped economy and the AI knowledge divide (33:29) Skills and mindset for future employees (38:04) Career ladders and AI's impact on entry-level jobs (40:10) HR's role in an AI-integrated work environment (41:10) Concerns and responsibilities with AI deployment (43:13) Closing remarks

EP23: The Agent Illusion: Why Most “AI Agents” Aren’t What You Think

What if the “AI agents” your organization is investing in aren’t actually agents at all? I woke up one morning, checked my phone, and saw yet another company announcing they are now an “AI agent company.” I have seen it over and over again. Different vendors. Same claim. No clear definition. I walk through in this episode what actually separates a workflow, a copilot, and a true agent, and why that distinction matters more than ever. I also share real examples of where organizations are getting this wrong, and what happens when you layer AI on top of broken processes. This is not about chasing the next buzzword. It is about knowing what you are actually deploying, what you can trust it with, and whether your foundation is ready for it. Because putting AI on top of broken processes does not create transformation. It hides the problem until it shows up at scale. If we cannot define what we are deploying, we cannot govern it, trust it, or scale it. HIGHLIGHTS: * Why “AI agent” has become one of the most misused terms in tech right now * The critical difference between workflows, copilots, and true agents * How to tell if a system is actually reasoning or just following a pre-built path * The hidden risk of “agent sprawl” and why it mirrors the rise of shadow IT * Why most AI demos look smarter than the systems actually are * The real reason agents fail when deployed on outdated processes and bad data * What adaptive reasoning and memory actually mean and why they matter * The 5 questions every leader should ask before trusting any “AI agent” * Why clean data and validated processes matter more than the technology itself HOST BIO: Jason Averbook has spent thirty years watching the gap between where organizations say they are with technology and where work is actually happening. He has a name for it. He has a framework for closing it. And he built Now to Next to do exactly that. Now to Next is the AI studio Jason co-founded with Jess Von Bank in 2026 — built on practitioner intelligence, original research, and the conviction that human transformation precedes digital transformation. Always has. Always will. Before Now to Next, Jason co-founded Leapgen, acquired by Mercer in 2023, where he led global HR transformation strategy and the firm's generative AI practice. Earlier he served as CEO of The Marcus Buckingham Company, co-founded Knowledge Infusion through its acquisition by Appirio, and held senior roles at PeopleSoft and Ceridian. He has advised hundreds of Fortune 1000 companies, authored two books on the future of HR and workforce technology, delivered more than 1000 keynote presentations globally, and teaches as an adjunct professor at universities worldwide. He is consistently recognized as one of the top three thought leaders globally on the future of work. FOLLOW JASON AVERBOOK: Substack: https://substack.com/@jasonaverbook [https://substack.com/@jasonaverbook] X: https://x.com/jasonaverbook [https://x.com/jasonaverbook] LinkedIn: https://www.linkedin.com/in/jasonaverbook [https://www.linkedin.com/in/jasonaverbook] Instagram: https://www.instagram.com/jasonaverbook [https://www.instagram.com/jasonaverbook] YouTube: https://www.youtube.com/@nowtonextwithjasonaverbook [https://www.youtube.com/@nowtonextwithjasonaverbook] Facebook: https://facebook.com/jasonaverbook [https://facebook.com/jasonaverbook] (0:00) Introduction and defining AI agents (2:49) Categorizing AI agents and system paths (6:22) Use cases and historical evolution from workflows to agents (11:28) Architectural differences: Workflow vs. agent (15:18) Key features of genuine agents: Adaptive reasoning and memory (19:34) Real-world application: Enhancing HR efficiency (21:48) Questions to ask vendors about AI agents

EP22: The Embodiment Gap: Why AI Adoption Was Never the Goal

What if the reason AI investments are not delivering value has nothing to do with the technology itself? Across industries, organizations are pouring billions into AI tools, rolling out enterprise copilots, and tracking usage metrics that suggest adoption is rising. But the outcomes are not changing. Productivity is not shifting in meaningful ways. Decision making is not improving. And leaders are starting to ask why. In my sixth solo episode, I unpacked what I call the Embodiment Gap. The growing divide between organizations that are simply adopting AI tools and those that are truly redesigning work so humans and AI become better together. Drawing on recent research from McKinsey, Forrester, Gartner, BCG, Harvard Business Review, and the Journal of Accountancy, I explore why only a small fraction of AI initiatives are delivering transformative value and why the real barrier is not technology but human design. This episode reframes the conversation from adoption to embodiment and challenges leaders to rethink how they measure success, build trust, and prepare for the coming wave of agentic AI that will reshape how decisions are made inside organizations. HIGHLIGHTS: * Why only 1 in 50 AI initiatives are delivering true transformative value * The hidden difference between using AI, adopting AI, and embodying AI * Why tracking prompts and logins tells you almost nothing about real impact * The psychological barriers that cause most AI rollouts to quietly stall * What the “Silicon Ceiling” reveals about the real limits of enterprise AI adoption * Why the coming wave of agentic AI will force organizations to rethink governance and accountability * The dangerous risk of knowledge atrophy as AI begins to replace human judgment development * Why the companies that win with AI will not be the ones that deploy tools fastest but the ones that redesign work first HOST BIO: Jason Averbook is a globally recognized thought leader, advisor, and keynote speaker focused on the intersection of AI, human potential, and the future of work. He is the Senior Partner and Global Leader of Digital HR Strategy at Mercer, where he helps the world’s largest organizations reimagine how work gets done — not by simply implementing technology, but by transforming mindsets, skillsets, and cultures to be truly digital. Over the past two decades, Jason has advised hundreds of Fortune 1000 companies, co-founded and led Leapgen, authored two influential books on the evolution of HR and workforce technology, and built a reputation as one of the most forward-thinking voices in the industry. His mission is to challenge leaders to stop seeing digital transformation as an IT project — and start embracing it as a human strategy. FOLLOW JASON AVERBOOK: Substack: https://substack.com/@jasonaverbook [https://substack.com/@jasonaverbook] X: https://x.com/jasonaverbook [https://x.com/jasonaverbook] LinkedIn: https://www.linkedin.com/in/jasonaverbook [https://www.linkedin.com/in/jasonaverbook] Instagram: https://www.instagram.com/jasonaverbook [https://www.instagram.com/jasonaverbook] YouTube: https://www.youtube.com/@nowtonextwithjasonaverbook [https://www.youtube.com/@nowtonextwithjasonaverbook] Facebook: https://facebook.com/jasonaverbook [https://facebook.com/jasonaverbook] REFERENCES: McKinsey AI Research (March 2026) https://www.mckinsey.com [https://www.mckinsey.com] Forrester AI Usage Findings (February) https://www.forrester.com [https://www.forrester.com] Harvard Business Review (March–April Issue) https://hbr.org [https://hbr.org] Journal of Accountancy AI Research (March 1) https://www.journalofaccountancy.com [https://www.journalofaccountancy.com] Gartner AI Governance Research (March 1) https://www.gartner.com [https://www.gartner.com] BCG AI at Work Report (2026) https://www.bcg.com [https://www.bcg.com] (0:00) Introduction to the episode "The Embodiment Gap" (1:05) Transformative value of AI initiatives and research sources (3:19) Understanding AI: Usage, Adoption, and Embodiment (5:30) The silicon ceiling and its implications for AI adoption (7:13) Measuring improvements in AI and the importance of embodiment (11:08) Psychological needs and trust in AI adoption (15:44) The evolution to agentic AI and its organizational impact (19:03) AI's role in decision-making, accountability, and knowledge atrophy (23:13) Comparing future-built companies and laggards in AI adoption (24:13) Summarizing AI's importance and concluding thoughts