The AI Values Podcast

95% of AI projects fail, so why do agentic AI leaders keep winning? In Episode 22 of The AI Values Podcast, Edosa Odaro and Lindley Gooden sit down with Tim Carmichael, Chief Data Officer at Chalhoub Group and a former British Army officer, for a conversation that refuses the easy version of the agentic AI story. Tim's argument is uncomfortable for anyone who has quietly assumed hybrid workforce strategy is mostly a technology problem: it's a leadership problem first, decided by servant leadership, AI risk management, and whether entry-level staff are elevated or discarded. Expect a hard look at C-suite AI literacy, board AI literacy, and why the AI project failure rate keeps climbing even as AI adoption accelerates.Tim Carmichael is Chief Data Officer and a former British Army officer who later built an airline from the ground up. He now also works as an executive coach, known across the data and AI leadership circuit for his focus on servant leadership.LinkedIn Tim Car: https://www.linkedin.com/in/tim-carmichael-link/WHAT IS COVERED► Tim breaks pitching AI initiatives into three reactions: glazy eyes, rolly eyes, or sparkly eyes. He explains why chasing the sparkly-eyed leaders first is the fastest route to agentic AI adoption that actually sticks.► "Don't throw your brain away when you're using AI." Tim's warning lands squarely on the human supervision of AI debate, and why treating agentic AI as an intern, not a replacement, keeps leaders in control.► Entry-level jobs used to build careers on repetitive, predictable work. Tim argues leaders must now deliberately elevate what entry-level jobs teach, the questioning and the nuance, instead of just automating the routine away.► Why do AI projects fail at rates as high as 95 percent? Tim pushes back on the doom-laden framing and reframes the AI project failure rate question around whether leaders understand the problem they're actually solving.► From the boardroom to the call centre, Tim walks through what board AI literacy actually requires, and why "just because you can doesn't mean you should" is the working definition of ethics behind his own AI risk management decisions.⏰ Episode timestamps00:00 - Cold Open: Which Eyes Are You Making Right Now? 01:57 - Servant Leadership Is the Root of AI Leadership 06:15 - Agentic AI Pitches: The Glazy Eyes, Rolly Eyes, Sparkly Eyes Test 08:08 - AI Leadership as Translation: The Interpreter Approach 10:42 - Hybrid Workforce: Playing to Human and Machine Strengths 15:15 - Why 95 Percent of AI Projects Still Fail 19:53 - The One Leadership Quality Agentic AI Cannot Replace 33:00 - Humans Supervised by Machines: Where AI Governance Draws the Line #TheAIValuesPodcast #AIGovernance #AIRiskManagement #ResponsibleAI #podcast──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more about the Institute ◼ Co-Host: Edosa Odaro & Lindley Gooden

AI governance means little if judgement cannot keep up. Can a boardroom trust a deepfake that only needs to create doubt, not fool anyone completely?

In Episode 21 of The AI Values Podcast, Edosa Odaro and Lindley Gooden sit down with Professor Julie Wall to ask an uncomfortable question for anyone rolling out AI at scale: if a model can predict an outcome, does that mean it should be used to decide one? Wall researches deepfake speech detection and explainable AI, and contributes to AI standards at the British Standards Institution. Her argument: responsible AI is a leadership discipline, not a compliance checkbox. It's a timely conversation. Recent research has linked heavy AI reliance to a measurable decline in critical thinking at work, and Gartner has warned that treating AI agents as uniformly governable is a fast route to enterprise failure.

Wall's episode moves through the future of work, deepfakes and public trust, algorithmic bias against neurodivergent users, and who actually carries accountability when an AI system gets it wrong.

WHAT IS COVERED:

► Why judgement beats automation. Routine work is already automating: research, drafting, first-pass code. Wall's own words: "Our judgement becomes important. That will become the core value."

► Deepfakes do not need to convince you. They need to make you doubt. Wall points to a real case: a US school principal deepfaked into "saying" comments he never made.

► Accuracy is not accountability. Wall built an AI that detects credibility in voice patterns, and it worked. "Just because something can be predicted doesn't mean that it should be used."

► Bias hides inside "typical" behaviour. A tool built for a general cohort reads gaze aversion as disengagement. For neurodivergent students, it means the opposite.

► The one question every board should ask. Not whether the AI is accurate enough. Wall's answer: organisations should be prepared to use it responsibly.

⏰ Episode Timestamps

00:00 - AI Safety Begins With The Deepfake Judgement Question

05:41 - Responsible AI At Work: Judgement Becomes The Core Skill

14:05 - AI Ethics And Critical Thinking: Asking The Right Question

21:22 - Deepfakes Don't Need To Fool You, Just Create Uncertainty

25:16 - AI Governance And Accountability: Who Owns The Decision

27:22 - Algorithmic Bias And Neurodivergent Users: Measuring vs Understanding 32:26 - The Board's One Must-Ask Question On Responsible AI

34:24 - Why AI Literacy Makes The Future Look Brighter

#TheAIValuesPodcast #AIGovernance #AIRiskManagement #ResponsibleAI #podcast

─────────────ABOUT THE AI VALUES PODCAST:

The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.

🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.

◼ Find out more about the Institute

◼ Co-Hosts: Edosa Odaro & Lindley Gooden

AI governance is usually treated as a policy problem. Mat Mallett, who has led technology at board level from the UK Space Agency to a cancer charity he founded himself, says the real problem is that even he can't control generative AI once it's out in the world.In this episode of The AI Values Podcast, Edosa Odaro and Lindley Gooden sit down with Mat Mallett, a board-level technology leader whose career runs from the UK Space Agency to CTO/COO of Cancer Central, the AI health tech charity he founded, where he also led development of Scotland's NHS 111 app, for a conversation about what actually happens when AI moves from theory into the boardroom. Mat's argument is uncomfortable for anyone treating generative AI as a solved problem: these systems are still teenagers, prone to hallucinating with total confidence, and the only real safeguard is human in the loop oversight, clear AI compliance expectations, and holding software vendors to account. Along the way the conversation covers AI-powered cyberattacks, deepfakes eroding trust on social media, what happens to personal data once AI can map it at scale, and why boardroom critical thinking matters more than ever as agentic AI edges toward autonomy.◼ Guest LinkedInWHAT IS COVERED: ► Mat Mallett says today's generative AI models are still teenagers. "They think they know everything… but they hallucinate badly," he warns, and explains why over-reliance on their outputs is his biggest AI safety concern right now.► AI-powered cyberattacks and deepfakes on social media: Mat on the "whack-a-mole" battle hackers are now winning with AI, and why AI-generated fakes are quietly reshaping public opinion.► What happens to your personal data once AI can map it at global scale. Mat explains the upside of AI-personalised recommendations, and the less obvious cost: a shrinking diversity of thought as algorithms cluster people who already think alike.► "We can't control generative AI," Mat says, and it's exactly why human in the loop oversight and software vendor accountability matter more as agentic AI edges toward full autonomy. Guardrails, he argues, look different for every business.► Inside the boardroom: how Mat reads the room when a board paper doesn't feel right, why critical thinking matters more than technical fluency, and his closing take on why quantum computing, not generative AI, is what genuinely excites him next.⏰ EPISODE TIMESTAMPS:00:00 - AI Governance in the Boardroom: Why We Can't Control Generative AI03:38 - AI Ethics From the UK Space Agency to Cancer Central05:01 - AI Safety Risk: Generative AI Hallucinates Like a Teenager06:20 - AI Deepfakes and Cyberattacks: The Governance Blind Spot14:08 - Data Privacy in a Fully Digital World 17:07 - Agentic AI vs Generative AI: Why Vendors Must Be Held to Account 19:44 - Responsible AI Leadership: Critical Thinking in the Boardroom 25:23 - Quantum Computing: The Next AI Breakthrough Mat Mallett Is Chasing #TheAIValuesPodcast #AIGovernance #ResponsibleAI #podcast #AgenticAI──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more about the Institute ◼ Co-Hosts: Edosa Odaro & Lindley Gooden

The future of AI will not be won by the richest countries. The UN warns it could split the world in two: are you ready for the divide, or the leapfrog?In Episode 19 of The AI Values Podcast, Edosa Odaro and Lindley Gooden take on one of the most contrarian questions in AI governance right now: does AI actually favour legacy economic power, or does it hand a genuine advantage to agile, fast-learning nations and organisations that the West assumed were left behind? Drawing on real examples of AI leapfrogging already underway, they challenge the assumption that AI regulation and AI policy will simply entrench the same countries and companies that led the last three technology waves.THIS WEEK: A HEAD-TO-HEAD. No guest this week, just Edosa and Lindley working the same problem from two angles: can leapfrog economies genuinely overtake legacy Western infrastructure, or is the UN's warned "next great divergence" already locking in a new global AI divide.WHAT IS COVERED► Edosa and Lindley open with a provocative reframe of AI governance: the advantage does not go to the richest countries. It goes to the fastest learners, and that changes who actually leads the future of AI.► They trace real leapfrog economies already in motion, from mobile phones overtaking landlines in Africa to solar power overtaking fossil infrastructure in Southeast Asia and fintech overtaking traditional banking in Latin America.► A mid-size health tech organisation built and rolled out a clinician-trusted diagnostic system faster than global medical giants could move. The lesson: agility beats legacy capital, and it is already happening in AI adoption.► The conversation turns to the UN's warning on "the next great divergence", the risk that legacy economies lock in a permanent AI monopoly while leapfrog economies are left with nothing left to jump over.► Edosa's closing line sums up the whole episode: "AI doesn't actually reward power. What it rewards is clarity." Clarity of purpose, data, process and values is the real foundation for responsible AI leadership, not raw compute.⏰ EPISODE TIMESTAMPS00:00 - Future of AI: Why Agility, Not Legacy Power, Is the Real Fuel00:24 - AI Governance's Old Assumption Gets Flipped: Nations Leapfrog Instead of Follow 00:50 - AI Policy Blind Spot: The Fastest Learners Beat the Richest Countries 03:16 - Why Legacy Capital No Longer Guarantees AI Dominance 06:00 - Agile Health Tech Beats Global Medical Giants: The Finland AI Lesson07:46 - Mobile, Solar and Fintech: How Leapfrogging Actually Happened Before 09:40 - The Next Great Divergence: The UN's Warning on an AI Monopoly12:14 - Clarity of Values, Not Power, Is What Lets You Leapfrog#TheAIValuesPodcast #AIGovernance #ResponsibleAI #podcast #AILeapfrogging──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more about The AI Values Institute ◼ Reach out: [email protected] ◼ Co-Hosts: Edosa Odaro & Lindley Gooden

AI governance is usually framed as risk mitigation. Lambert Hogenhout, the United Nations' Chief of Data and AI, says that's exactly the problem: we've gone from fifteen years to adjust to a new technology, down to fifteen hours.In this episode of The AI Values Podcast, Edosa Odaro and Lindley Gooden sit down with Lambert Hogenhout, Chief of Data, Analytics and Emerging Technologies at the United Nations Secretariat, for a conversation that starts with reinventing yourself for the age of AI and ends up somewhere nobody expected: happiness. Along the way it takes in AI risk management, the slow erosion of truth under "AI slop", and a pointed disagreement about whether the EU AI Act does enough. Lambert's argument is uncomfortable for anyone treating AI governance as a checkbox: real governance isn't only about stopping bad outcomes, it's about actively engineering good ones, and most current regulation only does the first half of that job.GUEST: Lambert Hogenhout is Chief of Data, Analytics and Emerging Technologies at the United Nations Secretariat, where he leads AI strategy, data governance and responsible tech policy across the UN system. He has 25 years' experience spanning the private sector, the World Bank and the UN, and is also an author and keynote speaker researching AI and human happiness.WHAT IS COVERED: ► Why the UN's AI chief says we're adjusting to new technology in fifteen hours, not fifteen years. Lambert explains why the honest response to that speed isn't faster adoption, it's more deliberate adoption, for individuals and for organisations. ► "Come on, that's not a job." Lambert on why nobody could have predicted search engine optimisation or social media influencer as careers in 1985, and why guessing at the jobs of 2031 is just as pointless now. ► AI slop, deepfakes and the slow erosion of truth: Lambert on why "you can't be sure that anything you see or hear is real" anymore, and what that does to trust at scale. ► Why Lambert thinks the EU AI Act gets governance half right. Risk mitigation matters, but he argues regulation also has to actively engineer for benefit, not just prevent harm, a distinction most AI governance frameworks miss. ► AI and happiness: Lambert's work applying psychologist Martin Seligman's PERMA model to technology adoption, and why the honest answer to "is AI making us happier" is currently no.⏰ EPISODE TIMESTAMPS:00:00 - The Future of AI Jobs Nobody Can Predict01:13 - Responsible AI Adoption Starts With What You Refuse To Automate04:19 - AI Governance and Reinventing Work for the Age of AI08:16 - Career Advice for the AI Generation: What To Study Now10:08 - AI Slop and the Erosion of Truth11:57 - Deliberate AI Adoption: 15 Hours, Not 15 Years 16:48 - AI and Happiness: What Adoption Is Actually For29:03 - The EU AI Act Debate: Why Risk Mitigation Isn't Enough #TheAIValuesPodcast #AIGovernance #ResponsibleAI #podcast #futureofwork ──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more about The AI Values Institute◼ Reach out: [email protected] ◼ Co-Hosts: Edosa Odaro & Lindley Gooden

52% of people now trust AI less than they trust humans with their data. On Episode 17, Edosa Odaro asks whether AI governance can survive a trust deficit this steep, and whether it's really the technology failing us, or the institutions behind it.This week, Edosa Odaro is joined by Tolu Adebekun for a head-to-head on the AI trust deficit facing UK boards, C-suite leaders and policy makers. Episode 17 argues that responsible AI has less to do with model sophistication than most leadership teams assume, and considerably more to do with the incentives, governance and accountability structures sitting behind the technology. Expect an uncomfortable case for why the Boeing 737 MAX, not the newest AGI headline, might be the more useful case study for your next AI governance conversation.THIS WEEK: A HEAD-TO-HEAD — Edosa Odaro and Tolu Adebekun take one problem, AI trust, and work it from two angles: the individual's choice to trust a system, and the institution's obligation to earn that trust.WHAT IS COVERED► Why AI trust has become a boardroom issue, not just a technology one. Edosa and Tolu unpack why institutional trust, not model capability, decides whether AI adoption actually holds inside an organisation.► "The systems don't yet have a mind of their own. They adopt the mind of their maker." Every major AI model reflects the incentives of the people who built it, with direct implications for AI governance and vendor accountability.► The Boeing 737 MAX as an AI risk management case study. The failure wasn't the software's intelligence. It was inadequate governance, training and testing, a pattern now shaping how boards think about explainable AI and oversight.► Can we actually control AGI? Edosa and Tolu work through incentives, autonomy and why "control" might be the wrong question to be asking about agentic AI right now.► Why AI regulation is a magnitude harder than social media regulation. Drawing on the Zuckerberg Senate hearings, the episode asks whether today's regulators are equipped for AI policy at all.⏰ EPISODE TIMESTAMPS00:42 - AI Governance Starts With Trust, Not Technology 03:21 - Why Institutional Trust Decides If AI Succeeds 15:08 - Trustworthy AI Depends On Who Actually Built It 16:01 - The Bottom Line Behind The AI Trust Deficit 21:42 - AI Regulation Is A Magnitude Harder Than Social Media 25:17 - Boeing 737 MAX: The AI Risk Management Lesson 28:40 - Does AGI Change Who's Actually In Control 31:34 - Can We Really Control AGI? AI Safety Under Pressure#TheAIValuesPodcast #AIGovernance #ResponsibleAI #podcast #aitrust ──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more: https://www.theaivalues.org ◼ Reach out: [email protected] ◼ Co-Hosts: Edosa Odaro & Tolu Adebekun

The biggest AI risk isn't hallucination, says Santiago Castro. It's expecting a generative tool to behave like a search engine.Edosa Odaro and Lindley Gooden sit down with Santiago Castro, Director of Data & AI Strategy at Pay.UK (the UK's retail payments authority) and formerly Global Head of AI & Automation at MUFG, to examine why so many organisations are still applying old, deterministic thinking to a new, probabilistic technology.The conversation moves between the short-term instinct to cut cost and the longer-term case for using AI to create value, and between individual boardroom groupthink and organisational values, and asks the question most boards are still avoiding: are you building your AI strategy to survive next quarter, or to still be relevant in five years?GUESTSantiago Castro, Director of Data & AI Strategy, Pay.UK. Formerly Global Head of AI & Automation, MUFG.————————————————————WHAT YOU'LL TAKE AWAY►"Why three different AI models giving three different answers to the same question is a feature, not a hallucination►"The "Company A vs Company B" thought experiment: why cutting half your people to deploy AI faster loses, long-term, to the company that keeps them and builds new value instead► How AI can take the ego out of boardroom groupthink, surfacing the thing everyone was thinking but wouldn't say out loud►"The one AI risk Santiago believes most boards haven't priced in yet► Why "digital first" and "data driven" have given way to "values driven," and what that actually means in practice⏰ EPISODE TIMESTAMPS00:00 - Cold open: "This is not a Google search"01:23 - Why old, deterministic frameworks can't explain generative AI03:44 - Assumptions, curiosity, and what "hallucination" actually means06:28 - Automation vs reinvention: the Uber and Airbnb AI lesson08:33 - Is AI the "holy grail" for cutting costs?09:16 - Company A vs Company B: the thought experiment every board should run12:57 - Taking the ego out of boardroom groupthink14:51 - The left-brain, right-brain case for AI as a playground, not a crutch19:16 - Where AI hits a hard stop: financial advice, guardrails, human-in-the-loop21:14 - The number one AI risk nobody's pricing in28:33 - Santiago's own AI agents, built from his favourite philosophers30:00 - "This is values driven": why digital-first and data-driven aren't enough36:16 - What typewriters and painting teach us about AI and jobs──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more The AI Values Institute◼ Reach out: [email protected] ◼ Get the Weekly AI Values Dispatch ◼ Co-Hosts: Edosa Odaro & Lindley Gooden

Gartner says just 1 in 50 AI investments deliver transformational value. So is this the AI bubble bursting, or the smartest money in the room?In Episode 15 of The AI Values Podcast, Edosa Odaro and Lindley Gooden go head-to-head on the question every board is quietly asking: is the AI investment boom built on value, or on belief? With global AI spend racing past $2.5 trillion, the conversation cuts through the AI hype to separate the AI ROI that's real from the AI valuation that's just expectation, using the dot-com boom and the Victorian railway mania as the cautionary tale.THIS WEEK: Just Edosa and Lindley working one problem, the AI bubble question, from two different angles: governance and accountability versus personal, human value.WHAT IS COVERED► There are two AI economies running at once. One is value-based, built on real productivity gains. The other is expectation-based, built on valuation and hype. Most boards are only watching one of them.► The railway investment boom is the closest historical parallel. Enormous capital flooded in, but not every line got built, and not every line that was built ever delivered a return. Sound familiar?► "So valuable we wish we'd never asked the question whether it's worth it." That's Edosa's bar for genuine AI value, and it's a much higher bar than most current AI deployments clear.► AI washing gets called out directly. Sticking an "AI-driven" label on everything doesn't create AI ROI, it just adds noise to a market already struggling to tell value from belief.► Lindley makes the case that AI value is ultimately personal, not just organisational. Fewer chores, more room for the things that matter, that's the test that actually drives adoption.⏰ EPISODE TIMESTAMPS00:01 - The AI Bubble: Branding Exercise or Real Value? 00:35 - AI Investment and the Railroad Analogy 01:47 - AI Washing and the AI Hype Problem 03:29 - Not Every Railway Got Built: A Warning for AI Investment06:16 - Two Currencies: Value and Belief in the AI Economy 09:01 - AI ROI: Value Economy vs Expectation Economy 12:01 - Balancing AI Benefits Against Hidden Risk 12:36 - Closing Reflections──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more about The AI Values Institute ◼ Reach out: [email protected] ◼ Get the Weekly AI Values Dispatch ◼ Co-hosts: Edosa Odaro & Lindley GoodenListen to the The AI Values Podcast on:◼ Youtube◼ Apple Podcast

89% of UK organisations are deploying agentic AI. Only 21% have mature AI governance to match. What happens when you automate to death, and who pays?

In Episode 14 of The AI Values Podcast, Edosa Odaro and Lindley Gooden are joined by Ming Tang, former Chief Digital, Data & Technology Officer at NHS England, for one of the most grounded conversations this podcast has produced on what responsible AI leadership actually demands. No hype. No techno-optimism. Just hard-won evidence from one of the most consequential AI and digital transformations in UK public sector history, applied directly to the decisions every board and C-suite faces right now.

GUEST: MING TANGMing Tang is a senior digital, data, and technology leader with a long track record of delivering large-scale transformation and value through modern digital platforms, data, and AI-enabled services. She led digital technology and data for NHS England, one of the largest technology functions in the entire UK government, and drove the work to create a digital-first NHS, encompassing AI diagnostics, electronic records, and national cybersecurity resilience.

WHAT IS COVERED

► "I want AI to do my washing, not my creative writing." Ming Tang draws the line most organisations miss: what AI should do, and what it should never touch. Get this wrong and everything starts to sound the same.

► The fallacy of efficiency. Automating what you already do doesn't create value. It locks you in. Ming Tang on why efficiency without a reimagined outcome is a strategic trap, backed by what she saw at the NHS.

► Human in the loop, NHS-style. Ming Tang's team built a four-agent framework to run checks inside clinical pathways. The human doesn't review every output. The human decides where the risk is. That's the difference.

► The pre-mortem question. Before you deploy, ask: what don't you want AI to do to your organisation? Ming Tang says most boards skip this. She thinks it's the most important question in the room.

► Cybersecurity is the agentic AI risk nobody is taking seriously enough. Bad actors are deploying millions of agents to probe your weak points. One gets through, and millions get paid. Ming Tang on why "doing more than the minimum" is now the floor, not the ceiling.

⏰ EPISODE TIMESTAMPS

00:00 — AI Governance in the NHS: What Should AI Never Be Allowed to Do?

03:03 — Ming Tang's Career, From Pharmaceuticals to NHS England

06:58 — AI Augmentation vs. Replacement — What Does the Ideal Look Like?

13:29 — The Fallacy of Efficiency: Why Automating to Death Locks Your Organisation In

18:30 — Entry-Level Jobs, Critical Thinking, and the Generation AI Is Quietly Leaving Behind

24:39 — Human in the Loop in Healthcare: The NHS Framework for AI Accountability

32:20 — Cybersecurity, Agentic AI, and Why C-Suites Are Still Unprepared

39:46 — Leadership Now: "What's One Decision You Need to Make Right Now?" Ming's Answer

──────────────────────────────────────

ABOUT THE AI VALUES PODCAST:

The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙

SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.

◼ Find out more about The AI Values Institute

◼ Reach out: [email protected]

◼ Get the Weekly AI Values Dispatch

◼ Co-hosts: Edosa Odaro & Lindley Gooden

AI values are not created by AI capability alone. 95% of enterprise AI fails to deliver measurable ROI. The real problem is not the technology: it is alignment, leadership, and whether anyone in your organisation has actually defined what value means.In Episode 13 of The AI Values Podcast, Edosa Odaro is joined by data and AI professional Tolu Adebekun, stepping in for regular co-host Lindley Gooden. What follows is a sharp conversation about the gap between what organisations invest in AI and what they actually get back. This episode addresses the core failure of AI organisational alignment: the assumption that capability automatically produces value. It does not. And the downstream consequences, from fragmented organisations to concentrated power in very few hands, are playing out right now across every sector.THIS WEEK: A HEAD-TO-HEAD.

Edosa Odaro and Tolu Adebekun take two angles on one problem: if most AI initiatives fail, and if capability is not the same as value, what exactly is leadership responsible for?► The sliding scale of AI anxiety. Edosa argues that the residual concern most people carry about AI is not about models or benchmarks. It is about relevance: their job, their judgment, their future. This anxiety runs from entry-level workers to the C-suite, and most organisations are managing it badly.► The AI amplification effect. "If you were terrible before, now that you've got AI to magnify that, you're just going to be worse." Tolu names what the data confirms: AI amplification works in both directions. Organisations with strong governance are pulling further ahead. Broken ones are breaking faster.► The biggest misconception in AI. "More capability would automatically mean more value. Unfortunately, it absolutely does not." Edosa draws on the spear analogy to separate capability vs value AI strategy: a pile of spears does not feed your family. Only the outcome does.► Every AI system has AI trade-offs built in, and most leaders have no idea who decided them. Whether you are using Claude, ChatGPT, or a traditional tool, someone has already decided the balance between speed, visibility, automation, and human judgment.► AI power concentration is now the leadership question. Tolu puts it plainly: fewer than 100 people have the influence to build the systems that billions now use. "I don't know a time in the world where we gave a few people lots of power and it went really well." 00:00 - AI Values: What People Are Really Worried About With AI01:17 - AI Governance: The Sliding Scale From Experts to Everyday Workers08:14 - Responsible AI Leadership: When Individual Anxiety Becomes Organisational Risk10:37 - AI Change Management: Why COVID Is the Right Analogy for AI Disruption16:14 - AI Amplification Effect: Why Good Organisations Win More and Broken Ones Break Faster24:53 - Capability vs. Value AI: The Biggest Misconception in AI Explained42:41 - AI Trade-Offs: Already Built Into Every System You Use44:35 - AI Power Concentration: Less Than 100 People Deciding AI for All of Us──────────────────────────────────────ABOUT THE AI VALUES PODCAST:The AI Values Podcast is where leaders come to think clearly about the trade-offs behind AI adoption not just the opportunities. Hosted by Edosa Odaro (author, 'The Values of AI') and Lindley Gooden (author, 'The Future of Truth'), with weekly conversations at the intersection of AI, trust, governance, and the future of work.🎙 SUBSCRIBE to The AI Values Podcast for honest, rigorous conversations at the intersection of AI ethics, AI governance, and business leadership.◼ Find out more: https://www.theaivalues.org ◼ Reach out: [email protected] ◼ Get the Weekly AI Values Dispatch ◼ Co-hosts: Edosa Odaro & Lindley Gooden◼ Special guest: Tolu Adebekun