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How can organizations help people do their best work—and deliver better experiences for customers—in the age of AI? In this episode of DisrupTV, co-hosts Vala Afshar and R "Ray" Wang welcome Camilla Kring, founder of The Bee Society and author of Chrono Leadership, and Celia Fleischaker, CMO of Conga. Kring explains how chronotypes and biological rhythms influence energy, well-being, and performance—and why more flexible, chrono-inclusive schedules could benefit employees, families, and organizations. Fleischaker discusses AI’s impact on go-to-market strategy, the shift from SEO to answer engine optimization, and why AI’s value extends beyond individual productivity to improving handoffs across the customer journey. The conversation also explores how organizations can build trust through pricing, contracting, and execution; organize teams around customer outcomes; and bring strategy to life through integration and change.

In a turbulent, over-hyped, and deeply human AI era, what does it actually take to lead well? In this episode of DisrupTV, hosts R "Ray" Wang and Vala Afshar bring together four leaders whose work spans human psychology, national security crisis response, enterprise AI strategy, and M&A IT leadership — and who all arrive at the same essential insight: the technical and the human are not separate problems. Maria Ross, author of The Empathy Dilemma, reframes empathy as information gathering — a performance multiplier, not a distraction — and shares the five pillars of empathetic and effective leadership: self-awareness, self-care, clarity, decisiveness, and joy. She explains why clarity is itself an act of empathy, why ambiguity keeps people in survival mode, and what CEOs and boards should actually do differently to lead through change fatigue and workforce transformation. David Bray draws on his experience leading technology crisis response during 9/11 and the anthrax attacks to surface enduring lessons about agency, joy, and the tunnel vision that makes crises worse. He explains why teams that cannot find moments of lightness are neurologically unable to absorb what is coming next — and why the most powerful question a leader can ask in chaos is not what do we do, but why are we here and where do we want to go together. Hiral Chandrana, CEO of Veltris, makes the case that true AI ROI only materializes when you change the economics of specific industry workflows — not when you deploy AI broadly and hope for the best. He breaks down the healthcare opportunity (where 25% of a $4 trillion industry is administrative overhead), the emergence of physical AI in robotics and industrial automation, and why the CIOs who become genuine growth partners will be the ones considered for CEO and Chief Strategy Officer roles. Jason James, CIO of Aptos and author of Make IT Work, introduces the concept of Eclipse IT — the phase beyond shadow IT where AI is not lurking in the background but eclipsing every process and governance structure in the organization. He shares what the pre-deal secrecy phase of M&A really looks like, why no playbook survives first contact with reality unchanged, and why his hiring philosophy for turbulent environments is simple: I can beats IQ. Whether you lead people, deploy AI, navigate M&A, or simply want to understand what great leadership looks like in a world that has no historical playbook, this episode offers four of the most grounded and complementary perspectives DisrupTV has brought together in a single conversation.

In the landmark 450th episode of DisrupTV, hosts Vala Afshar and R "Ray" Wang bring together two guests who illuminate the future of work from opposite ends — one from the front lines of AI-powered customer experience, one from the science of what makes teams truly exceptional — and find a coherent argument running through both: the organizations that win will be those that combine disciplined AI deployment with the human habits that turn good teams into great ones. Dave Rhodes, CEO of Verint, shares what AI transformation actually looks like at the scale of 14,000 customers and tens of millions of contact center agents worldwide. He explains why the $700 billion in human capital powering the contact center industry is not a cost to be eliminated but a capability to be amplified — and why AI deployed surgically can become a retention strategy as much as an efficiency play. He walks through the wrap-up bot as one of AI’s clearest enterprise wins, shares a product intelligence story about detecting a bad manufacturing batch through conversation intelligence before most customers even called, and makes the case that CX data is becoming a strategic sensing layer for the entire organization, not just a contact center metric. Ron Friedman, psychologist and author of Superteams, shares findings from his study of more than 6,000 workers that identified the 8% of teams that qualify as truly high-performing — and the specific habits that separate them from everyone else. He breaks down how super teams manage time, energy, and attention differently; the one question great leaders ask in meetings that transforms them from status updates into collaborative problem-solving; why video calls may be costing you more cognitive energy than they are worth; why members of super teams exercise 84 more minutes per week; and what his latest research reveals about how super teams use AI twice as often as average teams — but smarter. Whether you lead a customer experience organization, build high-performing teams, or are simply trying to figure out how to use AI in a way that actually moves the needle, this milestone episode offers one of DisrupTV’s most practical and grounded conversations yet.

In Episode 449 of DisrupTV, hosts Vala Afshar and R "Ray" Wang bring together three thinkers whose work spans the enterprise and the individual, the organizational and the deeply human — and who arrive at the same essential warning: AI is not a tool to be deployed. It is a force that will reshape how companies create value and how humans think, whether we are intentional about it or not. Brian Solis and Dave Wright, co-authors of Infinite and leaders at ServiceNow, make the case that most enterprises are caught in the iteration trap — automating the past instead of building the future. They explain why CEOs must start with why rather than how, why the number one driver of AI ROI is reimagining end-to-end workflows rather than layering AI onto existing ones, and why the real transformation is relational and organizational — from org charts to work charts, from ROI to Return on Intelligence. They bring it to life through IKEA’s one-billion-euro pivot from cost-cutting to revenue creation, the ANZ bank story of reclaiming 600 FTEs worth of hidden capacity, and a clear-eyed look at the governance challenges of multi-agent systems. John Nosta, one of the world’s leading innovation theorists, shifts the lens from the enterprise to the individual. His concept of anti-intelligence challenges the assumption that AI is a smarter version of human thinking — human cognition and AI computation are orthogonal, not parallel. He introduces the distinction between iterative intelligence (using AI to deepen thinking) and cognitive surrender (using AI to replace it), shares clinical research on AI rebound showing that extended AI use can erode the skills it was meant to support, and proposes Activities of Daily Thinking as the human practice we may need to protect most urgently in an age that makes thinking optional. Together, they sketch a coherent arc from the enterprise to the individual: AI demands reinvention at every level — of business models, of workflows, and of how we relate to our own minds.

In Episode 448 of DisrupTV, host R "Ray" Wang brings together three thinkers whose work sits at the intersection of AI, leadership, governance, and global innovation — and who all arrive, from very different directions, at the same essential insight: the real competitive advantage in the AI era is not access to the technology. It is what you do with it. Frank Castora, CEO of Ollion, makes the case that execution is becoming cheap and differentiation is becoming expensive — and that differentiation comes from human judgment. He explains how to decide which parts of a workflow to automate, augment, or keep fully human, why AI pushes solutions toward the median and how to engineer against that, and why the premium in services will always belong to the human judgment layered on top of the model, not the model itself. He also introduces a simple but powerful rule: if failure requires an apology, a human must be in the loop. Janet Wong, an experienced public-company board director and audit chair, explains why AI is now a full-board responsibility and what that actually looks like in practice. She covers how governance responsibilities are distributed across committees, what minimum guardrails leading companies are putting in place ahead of formal regulation, and why boards need AI steering committees, incident response plans, and cost visibility dashboards — not someday, but now. Amos Winter, MIT professor and author of Global by Design, shifts the lens to physical innovation and emerging markets. He argues that the biggest growth opportunities — and some of the most urgent problems — sit in resource-constrained contexts, and that designing for them requires perspective above all else. Through the lens of the Honda Super Cub, his lab’s work on low-power irrigation emitters, and a three-part framework for evaluating innovation opportunities, he makes the case for innovations that are rigorously engineered for real constraints and that travel globally because of that rigor, not despite it. Whether you lead a company, sit on a board, or build products for the world, this episode offers a clear-eyed playbook for deploying AI wisely, governing it responsibly, and designing for the markets that matter most.

Christopher Lochhead makes the case that the doom is manufactured and the opportunity is real. He walks through the actual data on new business formation, unemployment claims, and prediction market odds — and argues that the U.S. is in a phase of massive entrepreneurial building, not collapse. He then traces the AI economy’s parallel to the early internet, makes the case for the creator capitalist mindset (tiny teams, massive leverage, net-new categories), and introduces Invest America accounts as potentially the most powerful wealth-gap tool ever created — one that turns every child into an owner from birth through index-fund compounding and family contributions, with no intermediaries taking a cut. Neal Schore shifts the lens from external opportunity to internal constraint. His argument: most leaders don’t lack time — they leak it. Through the concept of the swirl — the mental loops of replaying conversations, assuming hidden threats, and defending against scenarios that don’t exist — he shows where the 25th hour actually disappears. He shares practical tools for solving intent before reacting, recognizing when fear is governing your behavior, and breaking the deeply embedded patterns that limit performance at every level of leadership. Together, they trace a coherent through-line: the constraint on human and organizational potential is almost never what the headlines say it is. Economic realism, ownership-centric thinking, and deep self-management may be the real competitive edge in the AI era. Whether you’re a founder, investor, executive, or simply trying to think more clearly about the economy, AI, and your own leadership, this episode offers the rare combination of data-grounded optimism and deeply practical behavioral insight.

Most people still think of Steve Jobs’ time at NeXT as a lost decade — an expensive detour between the original Apple story and the triumphant return. In this episode of DisrupTV, hosts R Ray Wang and Esteban Kolsky sit down with two guests who know that chapter better than almost anyone to make a very different argument: the NeXT years were the crucible that forged the Steve Jobs who came back and saved Apple, and the source of technology that still runs the devices in your pocket today. Geoffrey Cain, whose previous books include Samsung Rising and Perfect Police State, digs into newly uncovered archives to tell the real story of the NeXT years: the emotional devastation of being fired from the company he built, the audacious 3M computer vision, the perfectionism that made the NeXT Cube a commercial disaster, the partnerships with IBM and others that nearly changed the course of tech history, and the software — NeXTSTEP and WebObjects — that quietly became the foundation of everything Apple builds today. Dan’l Lewin was there. He joined NeXT as a co-founder after running major parts of Apple’s business, watched the partnerships collapse in real time, and eventually resigned because he didn’t believe Jobs was ready to change. He draws a sharp distinction between a boss — who controls everything and demands compliance — and a leader — who works in the open and empowers others — and describes the precise moment after Jobs’ return to Apple when he knew the transformation had finally happened. He also makes the case for NeXT’s edge-computing philosophy as one of the most prescient and enduring ideas in the history of Silicon Valley. Together, they trace the arc from angry founder to humbled visionary, from hardware failure to software breakthrough, and from a company that nearly went bankrupt to the acquisition that produced the greatest business turnaround in tech history.

What separates the companies that will define the AI era from those that will be displaced by it? In this episode of DisrupTV, hosts R "Ray" Wang and Vala Afshar bring together two guests with very different vantage points on the same question — one from the front lines of AI-first transformation, and one from the deeply human side of leadership development. Alejandro Laplana, CEO of Shokworks — the AI-first digital transformation consultancy behind work for HBO, FC Barcelona, and the United Nations — makes the case that the traditional services model is being fundamentally disrupted. The billable hour is giving way to gain-share arrangements where vendors win only when clients win. Middle-market companies ($50M–$500M) are using AI to achieve leverage that once required billions in investment. And the real efficiency gains aren’t in headline automation — they’re in eliminating the coordination tax buried in middle management layers and compliance workflows. He also draws a crucial distinction between operational AI, which improves today’s business, and innovation AI, which builds tomorrow’s competitive moat. Claire Díaz-Ortiz, who co-authored Why Can’t They Be Like Me? with legendary executive coach Marshall Goldsmith, explores the leadership trap that quietly caps most organizations’ potential: the assumption that what made you successful should work for everyone around you. She explains why homogeneity is innovation’s enemy, where AI genuinely helps in leadership development and where it falls short, and why the strengths that build careers can become the blind spots that limit leadership — if they go unexamined. Together, they trace a through-line from business model disruption to the human transformation required to lead through it: outcome-obsessed strategy on one side, and the perspective-rich, deliberately curious leadership needed to execute on the other.

What does it actually take to win with AI at the enterprise level — and what does it mean for society as AI becomes inseparable from how we live, work, and relate to one another? In Episode 444 of DisrupTV, hosts R Ray Wang and Vala Afshar bring together two leaders at the front lines of those questions from very different vantage points. TVN Reddy, CEO of Aptean — a vertical enterprise software company serving more than 10,000 customers — shares what AI adoption actually looks like at the front line of business. He explains why most organizations are caught in the action trap, burning tokens without creating outcomes, and why the shift from selling tools to selling results is fundamentally rewriting the enterprise software model. He introduces the 90/10 rule for competitive differentiation, makes the case for hiring AI-native engineers whose job is to feed agents work rather than do work themselves, and explains how ecosystems of agents — not single agents — are how you get from 60% accuracy to 99%. Lee Rainie, who spent nearly 25 years leading Pew Research’s internet and technology work and now directs the Imagining the Digital Future Center at Elon University, brings a societal lens to the same transformation. His research asks how humans will cope with the disruptions AI brings — and his answer may surprise you: resilience must start with institutions, not individuals. He introduces the concept of existential literacy, explains why AI may consume our solitude, and makes the case that deliberate friction — pause points built into AI-augmented workflows — may be essential to preserving human judgment, creativity, and agency. Together, they trace a through-line from enterprise outcomes to civilizational resilience, and close with a line that reframes the entire conversation: we are the last generation that will know what human capability felt like before it became inseparable from AI.

Charlene Li makes the case that AI is a leadership and strategy test, not a tech rollout — and that most organizations stall because they hand AI to IT instead of owning it as a CEO-level priority. She explains why leaders should kill their pilots, why speed has become the real competitive moat, and why the smartest companies are using AI for value reclamation — building new capabilities and services — instead of just cutting headcount. She also lays out the four building blocks of AI fluency: mindset, skill set, tool set, and decision set, and makes the case for a dedicated AI value owner who keeps the whole organization moving at the same tempo. Sebastian Wernicke shifts the conversation to the foundation underneath all of this: data. He argues that most data initiatives fail not because of bad tools, but because organizations misunderstand data’s actual purpose — which is change, not dashboards. He debunks three persistent myths — that data is objective, that it speaks for itself, and that it provides clean, definitive answers — and explains why psychological safety, not better software, is what actually lets data change minds inside an organization. Together, Li and Wernicke offer a practical, unified roadmap: clarify your strategy, empower real ownership, invest in fluency, and build a culture where data — and leaders — can be wrong in public without consequence.

Patricia Martin introduces the concept of persona fog — a civilizational malady born from a decade of curating ourselves for algorithms, where our online persona becomes load-bearing and our true self becomes hard to access. She explains why AI may become the most colossal persona fog machine we’ve ever encountered, capable of getting you, amplifying you, and optimizing you until it authors versions of you that you never intended. And she offers a counter-move: self-determination, integration, and becoming the editor-in-chief of your own identity. Tom Rath challenges the conventional wisdom of follow your passion, arguing it centers the self instead of contribution and relies on a tiny pinhole of life exposure. Drawing on his new book, he reframes purpose as something manufactured daily — in the lab of our daily choices — and shares a simple, practical heuristic, what’s the point?, that he uses multiple times a day to reorder his life around what matters. He also opens up about living with cancer for over 30 years, post-traumatic growth, and why you should never fully retire from contributing. Together, Martin and Rath offer a dual lens on the AI era: how we’re being fragmented and performed, and how we can rebuild our lives around contribution, daily choices, and the people who truly see us.

How do companies create entirely new markets—and why are the best organizations rethinking profit, trust, and corporate purpose? Join us for a thought-provoking conversation with Bruce Cleveland, author of Market Engineering, and Eric Ries, author of Incorruptible. We’ll explore what “Market Engineering” really means and why companies must actively shape markets to stay ahead, why trust has become one of the most valuable assets an organization can build, and how mission-driven companies outperform during times of disruption. We’ll also discuss why the era of shareholder primacy is being challenged, what comes next for corporate leadership, and how AI governance, healthcare, climate markets, and corporate accountability are reshaping the future of business. If you care about the future of leadership, innovation, and building enduring companies in the AI era, you won’t want to miss this one.

In this episode of DisrupTV, hosts Vala Afshar and R “Ray” Wang are joined by Malcolm Turnbull, Lucy Turnbull, Dr. David Bray, and Sheri Jacobs for a wide-ranging conversation on the future of AI, geopolitics, governance, and leadership. Together, they explore how artificial intelligence is reshaping global power structures through energy and infrastructure, why disinformation and synthetic media threaten shared reality, and how boards and executives must rethink risk in an interconnected world. The conversation also dives into a powerful leadership theme: trust and boundaries. From geopolitics to organizational design, the panel reveals why clarity, ethical structure, and defined limits are not constraints — but essential drivers of innovation and resilience in the AI era. This episode offers a critical roadmap for leaders navigating the intersection of technology, power, and human judgment in a rapidly accelerating world.

What happens when intelligence is no longer exclusively human? In DisrupTV Episode 439, Vala Afshar and R "Ray" Wang are joined by internet pioneer Vint Cerf, Dr. David Bray, and decision scientist Cheryl Strauss Einhorn for a far-reaching conversation on agentic AI, governance, misinformation, autonomous systems, and the future of human judgment. Together, they explore: Why agentic AI changes the rules of accountability and governance The rise of digital labor and human + agent collaboration How synthetic media and misinformation are reshaping enterprise risk Why critical thinking may become the most important skill of the AI era The role of human judgment, values, and decision-making in a world increasingly shaped by intelligent systems How organizations must redesign, reskill, redeploy, and restructure for the future of work From autonomous vehicles and synthetic data to cognitive fitness and decision science, this episode explores what it truly means to lead in an era where AI can act, reason, and scale alongside humans. The conclusion: AI may accelerate intelligence, but human judgment remains the ultimate competitive edge.

What do values and organizational truth have to do with AI success? In this episode of DisrupTV, Vala Afshar and R "Ray" Wang are joined by Paul Ingram, Columbia Business School professor and author of What Do You Really Stand For?, along with Jon Reed, co-founder of diginomica, for a deep conversation on leadership, AI, and the critical importance of context. Topics include: Why values are a leadership performance advantage The hidden “verification tax” hurting enterprise AI readiness Why the context layer may determine AI success or failure The limits of LLMs without governance and organizational truth How AI amplifies both clarity and dysfunction inside organizations This episode explores the intersection of human judgment, enterprise trust, and AI strategy—and why the future belongs to organizations that understand all three.