Now to Next with Jason Averbook

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

EP21: The Entry Level Collapse and the Rise of 22nd Century Leadership with Heather Jerrehian

What if by automating entry level work, we are quietly eliminating the future leaders we will need in five years? As AI accelerates productivity across enterprises, I see a silent fracture forming beneath the surface. Entry level roles are disappearing. Internships are evaporating. And Gen Z unemployment and underemployment are rising at rates that far too few leaders are openly discussing. In this urgent and deeply personal conversation, I sat down with Heather Jerrehian, Founder and CEO of H22 AI, to unpack what she calls an existential workforce crisis. From her vantage point in Silicon Valley, she has watched AI reshape workflows, hiring patterns, and corporate incentives in real time. What struck me most was this: the real danger is not automation itself, but redesigning work without redesigning pathways. Together, we explored an uncomfortable truth. Organizations may be breaking the very talent pipeline that built our own careers. As someone who teaches students and speaks with executives every week, I can feel the gap widening. This episode is a challenge to leaders, educators, and young professionals to rethink what career entry, leadership, and human AI collaboration must look like in a world that is moving faster than most systems can adapt. HIGHLIGHTS: * Why Gen Z unemployment and underemployment numbers signal a deeper structural shift * The hidden consequence of automating entry level work without redesigning it * What the Four Dimensional Workforce reveals that org charts cannot * Why transferable trust and proof of work now matter more than GPA * The uncomfortable truth about short term incentives versus long term talent health * How H22 is building a human AI collaboration platform for life and career navigation What leaders must redesign now before the talent gap becomes irreversible GUEST: Heather Jerrehian is an entrepreneurial futurist and the Founder and CEO of H22 AI, an AI native platform built to help Gen Z navigate life, learning, and career in an era of rapid technological disruption. Working at the forefront of social and technological shifts, Heather focuses on human AI collaboration and workforce intelligence. With H22, she is addressing the seismic impact AI has had on early career pathways by helping individuals build a sovereign blueprint of their strengths, motivations, and skills. Heather has built and scaled multi million dollar businesses as a serial founder, CEO, COO, and CFO. She led Hitch through rapid growth and a successful acquisition by ServiceNow. She is a Founding Limited Partner of How Women Invest, serves on Fast Company’s Executive Board, and is the author of the international bestseller Sail to Scale. Her mission is clear. Help the next generation find their reason for being and build toward a future where human potential and AI strengthen each other. 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 HEATHER JERREHIAN: LinkedIn: https://www.linkedin.com/in/heatherjerrehian/ [https://www.linkedin.com/in/heatherjerrehian/] (0:00) Introduction (0:09) Heather's background and non-traditional career path (3:15) Building a company for human AI collaboration (5:49) Gen Z focus and workforce challenges (8:02) Crisis for Gen Z in the workforce and AI's role (14:58) Four-dimensional workforce model and entry-level job restructuring (21:36) Urgency of addressing Gen Z employment issues (25:00) Employment's future and political implications (27:09) Mentorship, intergenerational collaboration, and AI in career development (32:22) Global economic impact of youth unemployment (35:07) Support strategies for Gen Z from employers and universities (39:09) Career advice for Gen Z and business leaders (45:37) Closing remarks

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

What if the biggest divide in your organization is no longer about role, pay, or seniority, but about how people think with AI? In this solo episode of Now to Next, Jason Averbook breaks down a pattern that is accelerating inside companies right now and largely invisible to traditional HR systems. Drawing from fresh labor data, market signals, and real examples from his own work, Jason introduces the idea of the K shaped AI economy where the split is not between jobs, but within them. He explains why two people in the same role can now be operating at radically different levels of impact, why performance systems are failing to detect it, and why AI fluency is no longer about using tools but about changing how work and thinking actually happen. This episode is a direct call to leaders, HR, and talent teams to stop planning for the future of work and start responding to the reality already unfolding. HIGHLIGHTS: * Why the AI driven K shaped economy is happening inside roles, not between them * How AI fluency is creating massive performance gaps within the same teams * Why performance reviews, engagement surveys, and training programs are missing the signal * The shift from AI adoption to AI embodiment and what that actually means * Why curiosity, not access or intelligence, is now the real barrier * How hiring, interviews, and talent assessment must change in an AI first world * Why buying more tools without changing mindset creates more risk, not less 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] (0:00) Introduction (0:14) Vibe coding anniversary and labor market split (0:35) SaaSpocalypse, software stock losses, and the K-shaped economy (1:30) AI adoption impact on productivity and performance management (4:07) AI fluency in future hiring and embodiment in the workplace (7:34) Rethinking learning, development, and AI integration in people strategy (10:07) Talent reassessment, early adopters, and upskilling (10:34) Tech adoption versus human transformation (11:22) Recap on the K-shaped economy and final thoughts (12:53) Closing remarks