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In AI Native: The Mandate to Transform Your Company, Kai-Fu Lee argues that real competitive advantage from AI does not come from buying access to the most powerful model, but from rebuilding the company itself around AI. Lee is the chairman and CEO of Sinovation Ventures, the founder and CEO of 01.AI, the former president of Google China, and the bestselling author of AI Superpowers. In his new book, he contends that AI is commoditizing human intelligence, making it the first and last intelligence revolution. He shows leaders how to move past common misconceptions, tap the dormant knowledge inside their organizations, and restructure teams so that small groups of people direct fleets of AI agents. In his conversation with Nikolaus Lang, global leader of the BCG Institute, he discusses the four flaws in how companies approach AI, why off-the-shelf models fail to solve a company’s hardest problems, the rise of the directly responsible individual, how leaders should think about AI costs, the uniquely human skills of future leaders, and whether AI poses an existential risk. Key topics discussed: 01:36 | Why AI is more fundamental than electricity or the internet 03:12 | The four flaws in how companies approach AI 06:20 | Why off-the-shelf AI won’t solve your hardest problems 11:03 | Tapping dormant data inside the company 13:32 | The directly responsible individual (DRI) and fleets of AI agents 18:15 | The end of traditional middle management 19:15 | How leaders should think about AI costs 22:49 | Taste, foresight, conviction, and courage: what remains human 26:46 | The elevator pitch for becoming AI native 27:43 | Is AI an existential risk? Additional inspirations from Kai-Fu Lee: AI Superpowers: China, Silicon Valley, and the New World Order (Harper Business, 2018)

In The CEO: The Role, the Reality, the Responsibility, Nitin Nohria argues that the CEO’s real work is not making the big decisions personally but building the conditions under which thousands of good decisions get made by everyone else. Nohria is the former dean of Harvard Business School, where he is currently the George F. Baker Professor of Administration, and for nearly 30 years he has run the invitation-only New CEO Workshop for recently appointed chief executives of the world’s largest companies. His latest book draws on that work, on empirical research into how much CEOs actually affect company performance, and on roughly 70,000 hours of data from real CEO calendars, to replace the myth of the heroic chief executive with a clear-eyed account of what the job involves: setting direction, allocating resources, shaping culture, managing stakeholders, and absorbing relentless scrutiny. In his conversation with Adam Job, senior director at the BCG Institute, Nohria discusses how much the person in the seat really matters, why new CEOs have to stop being COOs, where the hours in a CEO’s day actually go, how to tell a genuine crisis from daily noise, the structurally induced narcissism the role invites, what AI and geopolitics demand of this generation of leaders, and the one piece of advice he gives every CEO. Key topics discussed: 01:00 | How much the CEO in the seat actually matters 03:51 | Making decisions versus ensuring good decisions get made 06:19 | Why new CEOs struggle to stop being the COO 08:15 | The unexpected challenges of the job 10:19 | Inside 70,000 hours of CEO calendar data 13:18 | Whisper warnings, siren songs, and daily noise 16:21 | What CEOs must protect in their calendar, and what to cut 19:44 | Loneliness and structurally induced narcissism 23:59 | What AI and geopolitics demand of CEOs [26:42] How CEOs use AI, and the problem of AI slop [28:58] Why anyone would want the job [29:49] The single most important piece of advice Additional inspirations from Nitin Nohria: In Their Time: The Greatest Business Leaders of the Twentieth Century (Harvard Business Review Press, 2005)

In How Great Ideas Happen: The Hidden Steps Behind Breakthrough Success, George Newman argues that great ideas are not conjured from within but discovered outside of us, already present in the world, and that finding them is a methodical search anyone can run rather than a flash of genius reserved for a gifted few. Newman is a cognitive scientist and psychologist, and an associate professor of organizational behavior and human resource management at the Rotman School of Management at the University of Toronto, having previously held joint appointments in management, psychology, and cognitive science at Yale. In his first book, he draws on research across the arts, science, and business to recast creativity as an archeological dig: survey the terrain for fertile ground, grid the site, dig for volume, and only then sift for what is worth keeping. In his conversation with Adam Job, senior director at the BCG Institute, he discusses why organizations "turtle up" under pressure when they should be looking outward, why our best ideas arrive after we think we have run out, where AI genuinely helps the creative process and where it flattens it, the roughly 95/5 balance between proven ground and original twist, and why breakthrough ideas often feel uncomfortable at first. Key topics discussed: 01:01 | Reframing creativity as discovery rather than inspiration 02:38 | The archeology method: survey, grid, dig, sift 04:33 | Why organizations "turtle up," and how to stay outward-looking 06:13 | The creative cliff illusion: why the best ideas come last 08:35 | AI as an excavator: when it helps and when it doesn't 10:49 | Transplanting ideas from other domains 13:08 | The 95/5 balance of proven ground and original twist 16:13 | Ideas versus execution, and Steve Jobs' rock tumbler 19:36 | Creative hot streaks, from Jackson Pollock to Mondrian 25:14 | Why good ideas often feel uncomfortable at first 27:28 | How Newman applies his own research to his work

In Manage the Machine: How to Harness Human-AI Collaboration at Work, Paula Goldman argues that AI has crossed over from being a tool to being a partner, and that the companies that win will not be the ones automating the most or the fastest, but the ones that deliberately design around where humans still need to lead. Goldman is the first-ever chief ethical and humane use officer at Salesforce, where she is also EVP of Product, and previously led the Tech and Society Solutions Lab and impact investing at Omidyar Network. She has served on the US National AI Advisory Committee, chairing its generative AI working group. Her new book is a practical guide to integrating AI across functions from sales to HR to legal, setting out how to decide which tasks can safely be delegated to AI, which should stay with people, and what guardrails keep either from going astray. In her conversation with Adam Job, senior director at the BCG Institute, she discusses her "human at the helm" model of AI adoption, the role customer emotion plays in deciding where AI belongs, whether AI erodes the very human judgment it depends on, how to measure AI ROI beyond time saved, and what it takes to move from pilots to enterprise-wide rollout. Key topics discussed: 01:01 | What changes for leaders once AI shifts from tool to partner 02:28 | The "human at the helm" model in practice 07:09 | How the chief ethical and humane use officer role fits into AI governance 09:43 | Customer and employee emotion as a design input 12:39 | Skill decay: does the model erode itself over time? 15:54 | The jagged technological frontier and where to deploy AI 18:32 | Calculating AI ROI: cost savings versus new products 22:14 | Navigating two moving frontiers, better and cheaper 27:09 | Getting from successful pilot to enterprise rollout

In Global by Design: How to Create Innovations That Scale, Travel, and Transform, Vijay Govindarajan argues that the most powerful innovations are designed from the ground up for emerging markets like rural China or India, and then travel back to disrupt wealthy ones. Govindarajan is the Coxe Distinguished Professor at Dartmouth College’s Tuck School of Business and one of the world’s foremost experts on strategy and innovation, most known for the New York Times and Wall Street Journal bestseller Reverse Innovation. In his new book, co-authored with MIT engineer Amos Winter, he fuses business strategy with engineering science to show how high-value, low-cost products built for poorer countries can win there first and then upend established markets abroad, offering a roadmap for innovators across engineering, business, NGOs, and government. In his conversation with Nikolaus Lang, global leader of the BCG Henderson Institute, he discusses how GE built a $15,000 ultrasound machine for rural China; why most multinationals chase only the thin top slice of emerging markets; the three phases of his innovation framework; the difference between serial and parallel reverse innovation; and why globalization behaves like gravity even in a fragmented, multipolar world. Key topics discussed: 03:29 | How reverse innovation works: GE’s ultrasound machine for rural China 06:39 | Why most multinationals aren’t global by design 08:01 | The mistake of serving only the thin top slice of emerging markets 10:00 | Phase 1, elucidating requirements: P&G’s 3,000 hours redesigning a razor 13:00 | Phase 2, closing the innovation gap: GE’s low-cost CAT scanner 16:48 | Phase 3, serial vs. parallel reverse innovation 20:20 | Value-driven innovation, the Segway cautionary tale, and where the biggest opportunities lie 24:14 | Global by design in a geopolitically fragmented world Additional inspirations from Vijay Govindarajan: Reverse Innovation: Create Far From Home, Win Everywhere (Harvard Business Review Press, 2012) LinkedIn: Three Box Solution Weekly Column

In Blue Ocean Strategy: How to Create Uncontested Market Space and Make the Competition Irrelevant, Renée Mauborgne argues that lasting growth does not come from winning market share in crowded existing industries, but from creating entirely new market space that no one is competing in yet. Mauborgne is a professor of strategy at INSEAD and co-director of the INSEAD Blue Ocean Strategy Institute. Blue Ocean Strategy, co-written with W. Chan Kim has sold more than 4 million copies and is recognized as one of the most iconic and impactful strategy books ever written. The new 20th anniversary edition tests the original theory against today’s market realities and is enhanced with fresh cases, including NVIDIA’s three successive market-creating moves, a new preface that highlights the book’s ongoing global impact, and a curated list of over fifty blue ocean cases across diverse industries that expand far beyond those in the original version. In her conversation with Adam Job, senior director at the BCG Institute, Mauborgne discusses when a company should stop competing and start creating, why the search for new demand begins with non-customers rather than customers, how NVIDIA chases “zero-billion-dollar markets,” why differentiation and low cost need not be a trade-off, whether AI’s commoditizing effect makes advantage harder to defend, and how to reconcile bold commitment with the case for keeping options open. Key topics discussed: 01:12 | Why beating the competition is the wrong goal 02:34 | How to know when it’s time to shift from competing to creating 05:26 | Finding a blue ocean: value innovation and the role of non-customers 07:02 | Where the process starts inside an organization 09:25 | NVIDIA and the pursuit of zero-billion-dollar markets 12:46 | Breaking the trade-off between differentiation and low cost 16:21 | What prompted the new edition 18:33 | Will blue oceans stay defensible as AI commoditizes capabilities? 24:17 | Why using AI only for speed and efficiency is a trap 25:36 | Reconciling bold commitment with the need for optionality Additional inspirations from Renée Mauborgne: Blue Ocean Shift: Beyond Competing—Proven Steps to Inspire Confidence and Seize New Growth (Grand Central Publishing, 2017)

As uncertainty continues to define the business landscape, we’re revisiting our conversation with economist and complexity scientist Doyne Farmer on why conventional forecasting often falls short in a world shaped by interconnected, dynamic systems. Drawing on decades of research, he explains how complexity science offers a more realistic way to think about prediction, risk, and decision-making—and how leaders can navigate uncertainty with greater confidence. Whether you’re hearing this conversation for the first time or revisiting it with fresh perspective, Doyne’s insights remain as relevant today as ever.

In Crisis Engineering: Time-Tested Tools for Turning Chaos Into Clarity, Matthew Weaver and Mikey Dickerson argue that organizational crises are not problems to be survived but are rare windows in which rapid, directed transformation becomes possible within days rather than years. Weaver was a founding Site Reliability Engineer (SRE) at Google and later established the Defense Digital Service at the U.S. Department of Defense. Dickerson, also a founding SRE at Google, led the rescue of healthcare.gov, an effort that landed him on the cover of Time magazine. President Barack Obama subsequently appointed him deputy chief information officer of the United States, where he created the United States Digital Service. Together with their co-author Marina Nitze, the three are partners at the crisis engineering firm Layer Aleph. Drawing on decades of experience inside some of the most complex systems in government and industry—from the healthcare.gov rescue to wildfire response and pandemic logistics—the writers deliver a practical framework for identifying the five signals of a genuine crisis, and how to use that moment to drive lasting change across tech, government, healthcare, and beyond. In their conversation with Nikolaus Lang, global leader of the BCG Henderson Institute, they discuss why breakdowns in sensemaking cause well-trained operators to make situations worse, what the healthcare.gov rescue reveals about co-location and shared urgency, how crisis disrupts normal incentive structures to surface the organization’s real map, the concept of bracketing as a tool for directing team attention, and how AI integrations are creating the conditions for larger and harder-to-manage crises ahead. Key topics discussed: 01:24 | What “crisis engineering” means and what conditions define a true crisis 05:28 | Sensemaking: the invisible force driving decisions under pressure 10:38 | The 2013 healthcare.gov collapse: arriving on the crisis scene 14:05 | Why physical co-location is essential in a crisis 17:18 | Using a crisis to remap how the organization actually works 20:17 | Bracketing: deliberately defining the beginning and end of a crisis 25:33 | Why organizations struggle to define an exit condition 27:34 | Capturing crisis learning before returning to normal operations 30:22 | How AI is changing (and likely multiplying) crisis situations 35:51 | Advice for business leaders on building crisis readiness before a crisis hits

In The Irrational Decision: How We Gave Computers the Power to Choose for Us, Benjamin Recht argues that the optimization and mathematical rationality we apply to every corner of modern life—from dieting to hiring to strategy—often fails when encountering the messy realities of life. Recht is a professor of electrical engineering and computer science at UC Berkeley. In his new book, he traces how a narrow conception of rationality, born from 1940s wartime computing, came to dominate decision-making across society—and shows that this approach works brilliantly in closed, controlled systems like microchip design but breaks down in the complex, unpredictable domains where most real decisions are made. In his conversation with Adam Job, senior director at the BCG Henderson Institute, he discusses the origins of mathematical rationality, why optimization works for microchips but not for diets, why game theory fails to describe how humans actually behave, and how leaders should think about the boundary between human and machine intelligence in the age of AI. Key topics discussed: 01:02 | What is mathematical rationality and where do we encounter it? 02:49 | The origins of rational thinking in the 1940s 07:18 | Where optimization works: microchips, logistics, controlled systems 09:13 | Where it fails: Chernobyl, Waymo, and the limits of control 13:17 | When human “qualitative irrationality” is the right answer 14:59 | A framework for assigning decisions to machines vs. humans 17:45 | How the boundary between human and machine decision-making will evolve 19:14 | Why game theory fails to describe how humans actually behave 22:07 | Kahneman vs. Klein: two views on human decision-making 24:30 | What we risk losing as we outsource more decisions to AI

In AI Needs You: How We Can Change AI’s Future and Save Our Own, Verity Harding argues that AI governance is too important to be left to technologists alone—and that the rest of us need to join the conversation to shape this technology’s future. Harding is the director of the AI and Geopolitics Project at the Bennett School of Public Policy at the University of Cambridge and the founder of Formation Advisory. She spent more than a decade at Alphabet, first as head of Security Policy at Google, then as DeepMind’s first global head of Policy. In her book, she draws on historical case studies to show that democratic societies have successfully governed transformative technologies in the past. In her conversation with Nikolaus Lang, global leader of the BCG Henderson Institute, she discusses why the nuclear arms race is the wrong analogy for AI, what the 1967 Outer Space Treaty can teach us about cooperation between rivals, how Britain’s regulation of IVF became a gold standard by depoliticizing the technology, and what business leaders get wrong about their own role in shaping AI governance. Key topics discussed: 01:56 | Why the framing of AI as “too complex for nonexperts" is harmful 07:46 | Why the nuclear arms control analogy is counterproductive for AI 12:25 | The Space Race and the 1967 Outer Space Treaty as a model for cooperation 17:11 | IVF, the Warnock Committee, and why a philosopher led the regulation effort 20:38 | The internet: from open ideals to commercialization and surveillance 26:41 | What business leaders can do to shape AI governance 30:50 | Four principles for AI: peaceful intent, embrace limitations, purpose over profit, societal trust 35:25 | If you could mandate one thing for global AI governance, what would it be?

In Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great, Eric Ries argues that mission-driven companies face an invisible pressure that pushes them toward short-termism and conformity, no matter the intentions of their stakeholders. Ries is the best-selling author of The Lean Startup, founder of the Long-Term Stock Exchange, and advisor to startups around the globe. In his new book, he traces a recurring pattern across two centuries of business: principled founders build something exceptional, only to watch it be corrupted—not by greedy individuals, but by systemic forces baked into how capitalism is structured. In his conversation with Adam Job, senior director at the BCG Henderson Institute, Ries discusses how corporate corruption starts, why shareholder primacy became the norm, the concept of financial gravity, and the structural protections companies can put in place to defend their mission. Key topics discussed: 01:09 | How corporate corruption starts 03:50 | The rise of shareholder primacy 08:18 | Why mission-driven companies outperform but don’t dominate 11:06 | Are private equity and activist investors always destructive? 15:31 | Financial gravity: the invisible force that pulls companies off course 19:31 | Structural defenses: purpose, coherence, and integrity 27:06 | Can mature companies still be corrupted or still protect themselves? 31:14 | What Eric Ries would add to The Lean Startup if he could Additional inspirations from Eric Ries: The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses (Crown Currency, 2011)

In Inside the Box: How Constraints Make Us Better, David Epstein argues that constraints—not freedom—are what drive creativity, clarity, and focus. Epstein is a number one New York Times–best-selling author, known for Range and The Sports Gene. In his new book, he draws on psychology, economics, and case studies from NASA to Pixar to Dr. Seuss to show that our brains default to the path of least resistance—and that blocking that path is the only reliable way to force genuinely new thinking. In his conversation with Adam Job, senior director at the BCG Henderson Institute, he discusses why freedom is the enemy of creativity, how leaders can set constraints that unlock rather than stifle their teams, why creativity is not the same as originality, and how Herbert Simon’s idea of “satisficing” can improve both decisions and well-being. Key topics discussed: 01:03 | Why constraints drive creativity and freedom doesn’t 04:06 | What kinds of constraints to use and when they backfire 09:30 | Constraints in innovation vs. execution 13:08 | How to set constraints that maximize creativity without killing autonomy 16:34 | Why creativity is not the same as novelty or originality 19:29 | “Preregistering hypotheses” and how it applies to business 23:19 | Herbert Simon’s “satisficing”: choosing good enough over endless optimization 26:13 | How Epstein applies constraints in his own life and writing process Additional inspirations from David Epstein: Range: Why Generalists Triumph in a Specialized World (Riverhead Books, 2019)The Sports Gene: Inside the Science of Extraordinary Athletic Performance (Portfolio, 2014)

In Genius at Scale: How Great Leaders Drive Innovation, Linda A. Hill argues that innovation fails not because companies lack ideas, but because they struggle to scale those ideas across the enterprise—and that the solution lies not in structure or processes, but in leadership. Hill is the Wallace Brett Donham Professor of Business Administration at Harvard Business School, faculty chair of the Leadership Initiative, and one of the top ten management thinkers in the world as ranked by Thinkers50. In her new book, co-authored with Emily Tedards and Jason Wild, she draws on deep case studies of organizations from Mastercard to Pfizer to Pixar to show that scaling innovation requires three distinct but complementary leadership roles: architects, bridgers, and catalysts. In her conversation with Adam Job, senior director at the BCG Henderson Institute, she discusses why innovation labs alone don’t work, the ABCs of innovation leadership, how to build a culture of creative abrasion, and why even senior leaders need coaching to get innovation right. Key topics discussed: 01:28 | Why innovation fails at the point of scaling, not ideation 03:59 | The ABCs of innovation leadership: architects, bridgers, catalysts 06:29 | Getting metrics and incentives right for innovation 10:42 | What bridgers do and why organizations don’t have enough of them 14:33 | Is innovation leadership a team sport or a solo act? 18:48 | How to know which role you’re best suited to and how to learn the others 24:04 | How incumbent leaders can create urgency without being the new CEO Additional inspirations from Linda A. Hill: Collective Genius: The Art and Practice of Leading Innovation (Harvard Business Review Press, 2014)Article: Why Great Innovations Fail to Scale, co-authored by Emily Tedards and Jason Wild (March–April 2026 issue of Harvard Business Review)

In Design Love In: How to Unleash the Most Powerful Force in Business, Marcus Buckingham argues that love—not engagement, satisfaction, or motivation—is the only feeling that reliably changes the behavior of employees and customers, and that it can be deliberately designed into business. Buckingham is one of the world’s foremost researchers on human performance. He is a former senior vice president at Gallup turned New York Times–best-selling author, having written First, Break All the Rules. In his new book, he draws on decades of research to show that the relationship between experiences and outcomes is not linear—only experiences so positive that people describe them as “love” actually drive loyalty, productivity, and advocacy. In his conversation with Adam Job, senior director at the BCG Henderson Institute, he discusses why love is categorically different from engagement, the five feelings that make up a loving experience, three disciplines leaders can use to design love into their organizations, and why common practices like outsourcing and large spans of control are fundamentally unloving. Key topics discussed: 01:16 | Why love is categorically different from engagement or satisfaction 04:43 | The nonlinear relationship between experiences and outcomes 08:24 | How experiences drive behaviors that drive outcomes 12:34 | Designing love in: the five feelings and three disciplines 16:00 | Can love be designed into products, not just experiences? 19:13 | The three disciplines: walk the stage, equip the people, sequence the scenes 27:39 | Spans of control and the one-to-12 rule 30:17 | The limits of artificial experience–making Additional inspirations from Marcus Buckingham: First, Break All the Rules: What the World's Greatest Managers Do Differently (Gallup Press, 2016)

In this special episode, Rich Lesser, BCG’s global chair, and Martin Reeves, former chairman of the BCG Henderson Institute, reflect on the shocks and surprises that shaped the first half of the decade and what they reveal about the future. They explore the traits leaders need today: building trust, staying geopolitically aware, and adopting AI in a people-centered way.