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: podcast@theaivalues.org ◼ 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: podcast@theaivalues.org ◼ 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

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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: podcast@theaivalues.org

◼ 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: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch ◼ Co-hosts: Edosa Odaro & Lindley Gooden◼ Special guest: Tolu Adebekun

80% of data and AI products in organisations are never used. That is not a pilot problem; it is an AI value management crisis happening at scale right now.In Episode 12 of The AI Values Podcast, Edosa Odaro and Lindley Gooden sit down with Nicolas Averseng, Chief Product Officer at DataGalaxy and founder of Yui, one of the world's first dedicated AI value management platforms. This is one of the most practically uncomfortable conversations the podcast has produced. Nikola introduces what he calls "the fallacy of efficiency": the idea that the 30% productivity gains promised by agentic AI and GenAI deployments rarely materialise once they meet a CFO's scrutiny, and he explains why this trap catches even the most capable organisations. If your AI business case rests on efficiency gains, AI risk management, or responsible AI governance, this episode is required listening for your board.ABOUT NICOLAS AVERSENG:Nicolas Averseng is Chief Product Officer at DataGalaxy. He previously founded Yui, one of the world's first value management platforms for data and AI investments, which was acquired by DataGalaxy. He specialises in transforming data and AI governance from a compliance exercise into a genuine catalyst for value creation, and works with senior leaders globally to close the gap between AI investment and AI ROI.◼ Nicolas Averseng: https://www.linkedin.com/in/naverseng/WHAT IS COVERED:► The 80% problem: why the majority of data and AI products in organisations are never adopted, and the root cause most CDOs and boards refuse to acknowledge until it is too late► The fallacy of efficiency: how the promise of AI-driven productivity gains disappears when it meets the CFO's budget review, and why efficiency alone is the wrong objective for responsible AI implementation► The foundation-building trap: why organisations spend years building data platforms nobody uses, and how outcome-led AI implementation and minimum viable use cases change the equation entirely► AI value versus AI risk: Nikola's core argument, captured in his own words ("There is no value story without the downside"), explains why AI governance and AI risk management are not separate conversations, and how the EU AI Act is forcing this realisation even on organisations that resist it► The 14-month CDO problem: why chief data officers burn out before they deliver, what the average tenure of 12–24 months tells us about the state of AI value management, and what genuinely fixes it⏰ EPISODE TIMESTAMPS:00:00 — Cold open: years building a data platform nobody could use00:45 — Lindley introduces the 80% stat, what is it really costing us?04:49 — The foundation-building trap: why organisations build before they think08:15 — Starting from the end: the minimum viable AI use case approach12:09 — What does "value" actually mean? ROI vs. genuine user benefit16:40 — AI's wider cost: employment, ESG, client relationships, trust20:19 — The fallacy of efficiency: why GenAI's 30% promise rarely shows up24:26 — Are organisations getting better? 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: https://www.theaivalues.org ◼ Reach out: podcast@theaivalues.org ◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org◼ Edosa Odaro: https://www.linkedin.com/in/edosa/◼ Lindley Gooden: https://www.linkedin.com/in/lindleygooden/

What if your organisation's AI strategy rests on a system that doesn't understand the world the way you think it does?

Edosa Odaro and Lindley Gooden go head-to-head on Episode 11 of The AI Values Podcast on the debate that is quietly splitting the AI research world in two: LLMs versus world models, pattern recognition versus causal understanding, and the governance question that follows from the answer. This is not a technical forecasting conversation. It is the one your board should have before the next autonomous AI budget line gets signed.

WHAT IS COVERED:

► "The biggest problem around AI is that we speak about it as if it actually understands the world": why conflating language fluency with genuine understanding is the most dangerous assumption in AI governance, and what world models offer instead

► The transport company case study: an LLM correctly identifies a flood and reroutes an entire fleet, then causes gridlock, because it cannot model the downstream consequence of its own decision

► LLMs are not enough": why Lindley argues that without physical awareness, AI cannot be trusted in medical tech, sports science, or any domain where the real world pushes back

► Do AI systems need arms and legs? Why giving autonomous AI physical form is not an engineering decision but a values question, and why Silicon Valley's race to remove guardrails is precisely the moment human oversight matters most

► "I feel that we're giving human expectations to non-human systems": the framing that redefines AI alignment as a relationship risk, and what that means for every organisation deploying AI at scale

⏰ EPISODE TIMESTAMPS:

00:00 — The AI illusion: mistaking language fluency for genuine understanding

01:06 — LLMs vs world models: what the difference actually means in practice

02:09 — AGI and ASI: which architecture leads to general intelligence?

03:28 — Arms, legs, and autonomy: the embodied AI question nobody wants to answer

04:54 — Case study: the flood, the fleet, and the limits of LLM reasoning

06:35 — Silicon Valley, fewer guardrails, and the autonomy debate

08:03 — Causality, consequence, and what AI needs to understand an ecosystem

09:17 — "We're giving human expectations to non-human systems"

10:20 — Augmentation or transformation? The values-first answer

12:12 — A direct challenge: have this conversation in your own organisation

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: podcast@theaivalues.org

◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org

◼ Hosts: Edosa Odaro & Lindley Gooden

Most AI projects fail not because the technology fails, but because humans never fully integrate it into their way of working.

Amy unpacks what successful AI implementation really looks like, not from the tech side, but from the human side. From boardroom tensions to culture change, career disruption to lifelong learning, this is the conversation most AI podcasts aren't having.

THIS WEEK: A GUEST EPISODE

Our guest is Amy Shi-Nash, Professor of AI Practice at Monash University and Co-founder & CEO of Occupy. Amy brings more than two decades of hands-on implementation experience across global commercial organisations and academia — building AI that actually changes behaviour, not just processes. She is one of a rare group of practitioners who hasseen both sides: what makes AI succeed at scale, and why the human side is the part most leaders get wrong.

◼ Connect with Amy

⏰ EPISODE TIMESTAMPS:

00:00 — Cold open: "AI changes the shape of work, this is bigger than they say"

01:40 — Why 85–95% of AI projects fail to deliver value

05:00 — Meet Amy Shi-Nash: 25 years making AI work in large organisations

06:10 — What good AI implementation actually looks like (from the human side)

08:40 — The junction between humans and AI: why it determines everything

11:00 — From faster to different: culture change as the real measure of success

13:30 — Real-world examples: users building agents, evolving the system themselves

14:25 — Boardroom tensions: innovators, sceptics, literacy gaps, and time horizons

17:30 — Are we ready? The readiness question every board avoids

19:50 — Consequences: intended, unintended, and unevenly distributed

23:00 — The literacy imperative: AI education across every role and level

25:55 — Job composition change: what AI does and what humans must do

27:45 — Distribution of value: how AI reshapes the organisation's shape

29:00 — Flatter structures, specialist roles, fractional work, and the rise of the entrepreneur

32:00 — Debrief: culture, career paths, and the age of the specialised side hustle

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: podcast@theaivalues.org

◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org

◼ Co-Hosts Edosa Odaro & Lindley Gooden

Only 15% of organisations can put a hard number on the AI value they've delivered to their board. Not a technology problem a language one. This is where AI value gets lost.

In Episode 9 of The AI Values Podcast, Edosa Odaro and Lindley Gooden go head-to-head on one of the most uncomfortable diagnoses in AI leadership today: organisations aren't failing because the technology doesn't work they're failing because strategy, operations, and influence each speak a completely different dialect. And nobody is translating.

🎙 THIS WEEK: A HEAD-TO-HEAD No guest. Just two hosts, one research-backed problem, and a genuine divergence of views. Edosa brings the governance and leadership accountability lens. Lindley brings the communications, storytelling, and what-he-hears-from-senior-leaders lens. They find common ground exactly once and even that took 20 minutes.

📌 WHAT IS COVERED:

► Why only 15% of organisations can put a hard number on the AI value delivered to their board and what the other 85% are doing instead (McKinsey)

► The three languages of AI that fragment organisations: strategy, operations, and influence and why no one in the room is genuinely multilingual

► What Edosa Odaro calls "the value fog": the organisational blind spot in which AI value exists but is completely invisible to the people who need to see it most

► Why bad news about AI stops moving upward and why that silence is more dangerous than any technical failure: "Everyone stops talking. That is the issue."

► The case for an AI translator role inside organisations — the bridge function most businesses have not hired, named, or even defined yet

► The policy-versus-practicality disjoint: what senior leaders tell Lindley behind closed doors that AI has become disconnected from the rest of the business

► Whether agentic AI systems can solve the AI communication problem — or whether the lost language of AI value is fundamentally a human failure

► "Value has got to be the thing that brings everyone together and that language needs to be clear" where both hosts ultimately land, despite the disagreement

► What responsible AI governance actually requires from boards: not technical depth, but translatable clarity — and the cost of getting this wrong in 2026⏰

EPISODE TIMESTAMPS:

00:00 — Cold open: "The lost language of value"

00:38 — Edosa and Lindley introduce the episode

01:31 — The three languages of AI: strategy, operations, and influence

02:17 — Why aren't organisations multilingual?

03:07 — The research gap: 85% can't read the data; only 15% can report value to boards

07:35 — Should organisations build an AI translator role?

08:49 — Edosa introduces "the value fog" — AI value that exists but cannot be seen

11:43 — The CEO PhD debate: do leaders need to become more technical?

13:32 — Policy vs practicality: the AI disjoint Lindley hears from senior leaders

18:22 — Value as the unifying language — where the disagreement resolves

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: podcast@theaivalues.org

◼ Get the Weekly AI Values Dispatch → https://pages.theaivalues.org

◼ Cohost: Edosa Odaro & Lindley Gooden