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  • EP2: AI Is Moving Faster Than Your Operating Model with Johannes Sundlo

    EP2: AI Is Moving Faster Than Your Operating Model with Johannes Sundlo
    2026/10/05
    Six months can now make an AI idea go from sounding years ahead of its time to something people are already using every day. That compression creates a difficult question for executives: how do you make durable decisions when the technology, tools, and ways of working may change before a traditional planning cycle is finished?In Episode 2 of Now to Next: The Signal, the new season of Jason Averbook’s Now to Next podcast, Jason reconnects with Johannes Sundlo, a longtime HR practitioner who spent roughly 15 years inside organizations, including Spotify and Avalanche Studios Group, before focusing his work on AI, people, and organizations.Their conversation starts with agents but quickly becomes much bigger. Jason and Johannes explore what happens when employees bring personal agents into work, whether organizations are prepared for knowledge that moves with those agents, why long technology bets are becoming harder to make, and why data becomes even more important as the interface between employees and enterprise systems changes.They also confront a harder question for HR. If the workforce increasingly includes both people and machines, does it still make sense to organize HR and IT as separate worlds? Is another round of HR transformation enough, or is the function itself approaching a more fundamental redesign?This is a conversation about making decisions without pretending the environment is stable. The signals are already here. The question is whether executives are willing to redesign around them.HighlightsHow quickly agents moved from an emerging idea to something individuals are already using as part of everyday work.Why personal agents stop being purely personal the moment employees begin using them to perform work.What happens when an employee’s agent develops knowledge about the company and the employee eventually leaves.Why Jason believes organizations need to build a coordinated context layer so people can benefit from what the organization collectively knows.Why traditional long-term technology planning becomes harder when capabilities can change materially within months.Why Jason believes organizations should pay much more attention to signals than predictions right now.Why good data becomes more important as agents increasingly sit between employees and enterprise systems.How years of vendor lock-in, fragmented systems, and weak data practices create new constraints for HR.Whether the traditional separation between HR and IT still makes sense when organizations are managing both people resources and machine resources.Why another round of incremental HR transformation may not address the magnitude of the change now underway.Why leadership investment and psychological safety become more important, not less, when the technology is moving quickly.The difference between asking what AI could do and deciding what it should do inside a specific organization.Why practical experimentation matters more than claiming expertise in a field that changes almost daily.Jason’s argument that this is not another client-server-to-cloud transition, but a fight for relevance at the company, function, role, and individual level.Why the next employee experience may be defined less by navigating enterprise applications and more by agents acting across them.About Jason AverbookJason 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.About Johannes SundloJohannes Sundlo describes himself as a recovering HR person who spent roughly 15 years working inside organizations before turning his focus to AI and its implications for people and organizations.His HR career has included HR business partner and HR director roles, with experience at Spotify and as VP of HR for Avalanche Studios Group. Today, his work focuses on making sense of how AI is changing people, organizations, work, and the decisions companies need to make as these ...
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    1 時間 2 分
  • EP1: You Can’t Lead an AI Strategy You Haven’t Experienced with Alison McCauley

    EP1: You Can’t Lead an AI Strategy You Haven’t Experienced with Alison McCauley
    2026/09/17

    Most executives are being asked to make consequential decisions about AI before they have personally experienced what the technology can actually do. That creates a fundamental leadership problem: how do you set strategy for something you understand primarily through presentations, demonstrations, and other people’s explanations?

    In Episode 1 of Now to Next: The Signal, the new season of Jason Averbook’s Now to Next podcast, Jason sits down with Alison McCauley, two-time bestselling author and author of How to Think with AI, to examine the growing gap between what AI makes possible and what most enterprises are actually doing with it. Jason and Alison explore what that disconnect means for leadership, learning, trust, culture, work design, and the role of HR. They challenge conventional measures of AI adoption, examine what happens when employees understand the possibilities before leadership does, and ask how organizations should prepare for a workforce that increasingly includes both human and digital workers.

    The conversation ultimately moves beyond AI itself. It asks whether executives, operating models, and institutions can learn and change quickly enough to make intelligent use of a technology that will not wait for them to catch up.

    Episode Highlights

    • Why leaders need direct experience with AI before they can shape a meaningful strategy.
    • What changes when software learns from people instead of people learning the software.
    • Why the gap between personal and enterprise AI is becoming impossible to ignore.
    • How speed to learn can matter more than speed to launch.
    • Why login rates reveal almost nothing about whether work is actually changing.
    • What HR must do when the workforce includes both humans and digital workers.

    About Jason Averbook

    Jason Averbook has spent more than 30 years shaping HR technology and workforce transformation. His career includes leadership roles at PeopleSoft and Ceridian, co-founding and leading Knowledge Infusion from 2005 to 2012, serving as CEO of The Marcus Buckingham Company, and co-founding and leading Leapgen from 2018 to 2023. After serving as Mercer’s Global HR Transformation Leader, he co-founded Now to Next to help leaders prepare people and organizations for an AI-shaped world.

    About Alison McCauley

    Alison McCauley is a two-time bestselling author who has spent three decades operating as a conduit between Silicon Valley disruptors and enterprise leaders seeking to leverage new technology. As an adviser to both the enterprise C-suite and emerging technology founders, she has helped develop new market categories and partnered with early leaders in AI since 2010.

    As a social scientist, Alison’s work is grounded in human behavior, organizational dynamics, and the challenge of translating innovation into performance. Her most recent bestseller, How to Think with AI, grew from a year of research studying hundreds of AI early adopters and turns those insights into a framework for helping people use AI as a cognitive advantage. Her work has appeared in Harvard Business Review and Forbes, and her executive education course has reached more than 100,000 learners.

    Stay Connected

    Alison McCauley

    Website: https://www.alisonmccauley.io/

    LinkedIn: https://www.linkedin.com/in/unblocked/

    Jason Averbook

    LinkedIn: https://www.linkedin.com/in/jasonaverbook/

    X: https://x.com/jasonaverbook

    Substack: https://jasonaverbook.substack.com/

    Now to Next

    Website: https://nowtonext.ai/

    Podcast: https://podcast.nowtonext.ai/episodes

    LinkedIn: https://www.linkedin.com/company/now-to-next-ai/

    Instagram: https://www.instagram.com/nowtonext.ai/

    YouTube: https://www.youtube.com/@nowtonextai

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    43 分
  • Intro Episode for Now to Next: The Signal

    Intro Episode for Now to Next: The Signal
    2026/09/16

    Everyone wants to know which AI tool to buy, but far fewer people are willing to talk honestly about what happened after they bought it. After 28 episodes of his previous podcast, Jason Averbook is beginning a new season with a new name and a sharper purpose: Now to Next: The Signal. It is designed to be an hour without the noise, built around candid conversations with executives, technology leaders, and practitioners who are already doing the work of transformation.

    These conversations will go beyond polished case studies and easy slogans. Jason wants to understand how work actually changed, where organizations automated dysfunction, who was left behind, and what leaders still have not figured out. The goal is not to feed the fear or manufacture reassurance. It is to stay with the questions that matter, especially when the answers are not clear.

    This season is for CIOs, CXOs, CHROs, CEOs, transformation leaders, and anyone curious about people, technology, and the way the world is changing. The premise is simple: AI is not the transformation. You are.

    Episode Highlights

    • What changes after 28 episodes when the conversation gets more focused?
    • Why are so few people asking what actually changed after the AI arrived?
    • When does automation become dysfunction moving faster?
    • The most useful transformation conversations start where the easy answers end.
    • What remains uniquely human when machines can do more of the work?
    • The fear beneath the AI conversation may be the fear of becoming irrelevant.

    About Jason Averbook

    Jason Averbook has spent more than 30 years shaping HR technology and workforce transformation. His career includes leadership roles at PeopleSoft and Ceridian, co-founding and leading Knowledge Infusion from 2005 to 2012, serving as CEO of The Marcus Buckingham Company, and co-founding and leading Leapgen from 2018 to 2023. After serving as Mercer’s Global HR Transformation Leader, he co-founded Now to Next to help leaders prepare people and organizations for an AI-shaped world.

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    3 分
  • EP28: Giants Will Fall: Rewiring the Enterprise to Become AI-Native with Melissa Reeve

    EP28: Giants Will Fall: Rewiring the Enterprise to Become AI-Native with Melissa Reeve
    2026/07/15
    Most organizations are treating AI like a technology rollout. Buy the tool, train the team, check the box. Melissa Reeve has spent 25 years watching that exact playbook fail, from digital transformation to agile to cloud, and she wrote a book about why this time the stakes are even higher. In this episode, Jason and Melissa dig into why AI represents the largest management challenge in the last century and why giant brands will fall if they keep running on 100-year-old management thinking while AI-native startups are eating their lunch. Melissa breaks down the Hyperadaptive Model from her new book, a five-stage framework for rewiring how organizations actually operate, not just how they deploy technology.
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    39 分
  • EP27: Adaptability, Trust, and the Human Skills AI Can't Replace with Lara Albert

    EP27: Adaptability, Trust, and the Human Skills AI Can't Replace with Lara Albert
    2026/06/15
    What happens when AI can do more of the work we've traditionally assigned to people? For many organizations, the conversation quickly turns to automation, efficiency, and workforce disruption. But according to Lara Albert, the more important conversation is about adaptability. As AI continues to reshape how work gets done, leaders face a critical challenge: helping people develop the skills, judgment, and confidence needed to thrive alongside increasingly intelligent technology. The future will not belong to organizations that simply deploy AI. It will belong to organizations that help people evolve with it. In this episode of Now to Next, Lara Albert joins me to explore the realities behind AI transformation, workforce readiness, leadership responsibility, and the human capabilities that will matter most in the years ahead.
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    41 分
  • EP26: The Human Side of AI: Trust, Fear, and Why Change Management Must Change with Dr. Xenia Wade

    EP26: The Human Side of AI: Trust, Fear, and Why Change Management Must Change with Dr. Xenia Wade
    2026/06/05
    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.
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    45 分
  • EP25: The Trust Collapse: Why Your Workforce Has Stopped Believing Your AI Strategy

    EP25: The Trust Collapse: Why Your Workforce Has Stopped Believing Your AI Strategy
    2026/05/29
    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.
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    23 分
  • EP24: The Function Nobody Owned: HR, IT, and AI Finally in One Room with Tracey Franklin

    EP24: The Function Nobody Owned: HR, IT, and AI Finally in One Room with Tracey Franklin
    2026/04/23
    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.
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    44 分