AI Ethics & Responsible Technology

Why organisations work with Richard Foster-Fletcher Brings a structured research practice, run through MKAI and Reality & Reason, that publishes instruments organisations can use to test the integrity of management information once AI is in the loop. Has examined AI’s effect on disclosure and decision processes through a study of 150 SEC 10-K filings across 50 US public companies, giving a quantitative spine to claims most AI keynotes leave at the anecdote. Advises across an unusually wide institutional surface: UK Parliament, the United Nations Environment Programme, governments including Tunisia, and Fortune 500 boards, so the perspective is not single-sector. Treats AI ethics as an operating problem for governance, audit, and the executive, rather than a values statement, which is the brief most boards now actually need. Holds standing as a Favikon UK Top 20 AI Researcher and Entrepreneur and a LinkedIn Top Voice in AI, both reflecting sustained public output rather than a one-off ranking. Biography highlights Founder and Executive Chair of MKAI.org, a global responsible-AI organisation established in 2019. Founder of Reality & Reason, publisher of the Management Information Integrity Addendum and the Residual Logic Scanner. Author of the weekly essay series “What Still Matters,” with a subscriber base of over 6,000 senior readers. Former AI and CX Director at Oracle; earlier career at the BBC. Member of the United Nations Environment Programme Resilience Frontiers Advisory Group. Lecturer at LSE, UCL, Oxford, Imperial College London, Cranfield, and Henley Business School. Named in the UK’s Top 20 AI Researchers and Entrepreneurs by Favikon; LinkedIn Top Voice in AI. Qualifications from MIT Sloan (Implications of AI for Business Strategy) and the University of Michigan (Data Science Ethics). Biography Most organisations now have generative AI inside their writing, analysis, and decision flows. Few have a clear view of what that is doing to the quality of the reasoning the board ultimately sees. That gap is the territory Foster-Fletcher works in. Through MKAI, the responsible-AI organisation he founded in 2019, and Reality & Reason, his editorial and research body, he publishes practical instruments for senior teams. The Management Information Integrity Addendum and the Residual Logic Scanner sit alongside a study of 150 SEC 10-K filings across 50 US public companies, looking at how AI-shaped language enters formal corporate disclosure. His advisory footprint covers UK Parliament, the United Nations Environment Programme Resilience Frontiers Advisory Group, governments including Tunisia, and Fortune 500 boards. He lectures at LSE, UCL, Oxford, Imperial College London, Cranfield, and Henley Business School, and earlier in his career held senior roles at Oracle and the BBC. The signature contribution is a framework on the structural dynamics of enterprise AI adoption, which sets out seven recurring patterns including private accumulation of capability, erosion of human capacity through routine offloading, and the narrowing of visible strategic alternatives under model-led framing. That framework is what senior buyers are usually responding to when they commission him. Key speaking topics Responsible AI governance for boards and executive teams AI strategy beyond pilots and proof-of-concept AI in management information, reporting, and disclosure The future of work in the age of generative AI AI ethics as an operating capability Decision-making and human judgement when models are in the loop Leadership in an AI-shaped organisation Ideal for Boards, audit committees, and CROs wrestling with AI as a governance and disclosure question CIOs, CDOs, and Chief AI Officers moving from experimentation to operating deployment CEOs and executive teams in regulated sectors where AI is entering decision processes Government and policy audiences responsible for AI regulation, public-sector adoption, or capability building Audience outcomes A working language for what AI is doing to the integrity of internal information and decision papers A clear map of recurring failure modes in enterprise AI adoption, drawn from the seven-pattern framework A defensible point of view on AI governance suitable for board, audit, and disclosure conversations Concrete next moves on where AI should and should not be in the reasoning chain A grounded sense of the future of judgement, expertise, and human capability inside AI-shaped organisations

Why organisations work with Tia White Operator perspective from inside a hyperscaler. She runs go-to-market, product and engineering for an AWS AI portfolio tracking over USD 25M in profit, including some of the fastest-growing services at AWS. A track record of taking generative AI and personalisation from theory into customer-facing product. She led the introduction of Personalized Search, Next Best Action and generative AI capabilities into Amazon Personalize. Cross-sector enterprise fluency. Before AWS she held senior technology roles at Wells Fargo, Capital One and JPMorgan Chase, leading regulated digital transformation programmes in financial services. A specific point of view on what separates AI investments that compound from AI investments that stall, grounded in current AWS customer work rather than vendor abstraction. A credible voice on building the technical leadership bench behind AI, including women and Black technologists, that boards are now being asked to account for. Biography highlights General Manager, AI and Machine Learning, Amazon Web Services. First Black woman hired as a GM in Machine Learning, AI and Analytics at AWS. Director of Engineering at a Fortune 100 company before age 30. Prior senior technology roles at Wells Fargo, Capital One and JPMorgan Chase. Led the launch of new Amazon Personalize capabilities including Personalized Search, Next Best Action and generative AI features; speaker at AWS re:Invent 2022 on personalisation. Featured in Forbes; keynote and emcee credits include SXSW and the Grace Hopper Celebration. Board and advisory roles include Rewriting the Code. Biography Generative AI has moved faster than most enterprise operating models can absorb. Inside AWS, Tia White runs the AI and Machine Learning business that customers turn to when a pilot has to become a product. She owns go-to-market, product and engineering for an AI portfolio tracking over USD 25M in profit, including some of the fastest-growing services at AWS. Her work at AWS includes leading the next generation of Amazon Personalize, with features such as Personalized Search, Next Best Action and generative AI capabilities now used by enterprises to lift engagement and revenue. She has spoken at AWS re:Invent on personalisation as an operating discipline rather than a marketing feature, and is regularly cited by AWS as a voice on what Gen Y and Gen Z customers expect from personalised experiences. Before AWS she held senior technology roles at Wells Fargo, Capital One and JPMorgan Chase, including the leadership of public cloud migrations in financial services. She reached Director of Engineering at a Fortune 100 company before the age of 30. That financial services background gives her a working answer to the questions regulated industries are now asking about generative AI, data, privacy and risk. She was the first Black woman hired as a GM in Machine Learning, AI and Analytics at AWS, and uses that platform to address the harder question behind most AI roadmaps, which is whether the organisation has the talent and the leadership bench to deliver them. She has been featured in Forbes, has keynoted and emceed at SXSW and the Grace Hopper Celebration, and sits on boards including Rewriting the Code. Key speaking topics Generative AI in the enterprise Personalisation as a revenue and engagement discipline AI agents and agentic workflows Machine learning in regulated industries Cloud migration and digital transformation Responsible AI and bias mitigation Building diverse technical leadership in AI and engineering Ideal for CTOs, CIOs and Chief Data and AI Officers moving from AI pilots into production CMOs and Chief Customer Officers investing in personalisation, recommendation and customer engagement Boards and executive committees in financial services, retail and regulated industries setting AI strategy CHROs and DEI leads responsible for the technical talent pipeline behind AI Audience outcomes A clearer read on which generative AI use cases pay back and which do not, drawn from live AWS customer patterns. A working view of personalisation as an operating capability that touches data, product and engineering, not a marketing campaign. Sharper questions for the board on AI risk, privacy and the operating model around generative AI. A concrete sense of what the technical leadership bench behind a serious AI roadmap looks like, and where most organisations are short.

Why organisations work with Lorraine Hariton Six years leading Catalyst, the global nonprofit whose research and benchmarks Fortune 500 boards already use to evaluate their own progress on women’s advancement. Operating background that buyers in male-dominated executive teams take seriously: 15 years at IBM, CEO of two Silicon Valley start-ups, Obama-appointed State Department official. Specific authority on the measurement question. Catalyst’s frameworks on emotional tax, empathic leadership, and inclusion assessment were developed and scaled during her tenure. Credible on the intersection of bias and emerging technology, including how gender and racial bias enter AI systems through data and design choices. Biography highlights President and CEO of Catalyst from 2018 to 2024. Special Representative for Commercial and Business Affairs at the US State Department under President Obama. CEO of two venture-backed Silicon Valley companies, Beatnik and Apptera. Senior Vice President of Global Partnerships, New York Academy of Sciences; co-founder of the Global STEM Alliance and the 1000 Girls, 1000 Futures programme. Inaugural Women’s Leadership Champion Award, University of Virginia Darden School of Business, 2022. Crain’s New York Business Women of Influence, 2023. BS Stanford University, MBA Harvard Business School. Biography Catalyst is the research organisation whose data Fortune 500 boards quote back to themselves when they discuss the women-in-leadership gap. For six years that organisation was run by Lorraine Hariton, an operator with credentials those same boards understand: fifteen years at IBM, two CEO roles at venture-backed Silicon Valley companies, an Obama-administration appointment representing US commercial interests at the State Department. That mix matters because the audience for serious DEI work has shifted. Senior teams now want practitioners who can speak the language of operating performance and capital discipline, not advocacy. At Catalyst, Hariton oversaw the development of frameworks used inside member companies on emotional tax, empathic leadership, and inclusion measurement, the kind of artefacts that survive contact with a sceptical executive committee. Her work addresses the credibility gap between public DEI commitments and observable workplace outcomes. She speaks directly to the failure mode senior leaders fear most, performative policy that produces no change and erodes employee trust. She also works on how gender and racial bias enter AI systems through training data, an issue most executive teams are still under-prepared for. The University of Virginia Darden School of Business presented her with its inaugural Women’s Leadership Champion Award in 2022. Crain’s named her to its Women of Influence list the following year. Her holistic view of where women’s advancement sits within an organisation, alongside compensation strategy, capital allocation, and technology governance, is what makes her useful in a boardroom rather than at a conference panel. Key speaking topics Gender equity and women’s advancement in senior leadership Inclusion measurement and DEI accountability Bias in artificial intelligence and emerging technology Workplace culture transformation Future of work and flexible workplace design Empathic and inclusive leadership practice Ideal for CHROs, Chief Diversity Officers, and CEO offices commissioning a measurable advancement strategy for women in senior leadership Boards and nominating committees evaluating their own pipeline credibility Senior leadership teams in male-dominated industries (financial services, technology, energy, industrials) working on inclusion outcomes that hold up to scrutiny Companies building governance around bias and fairness in AI deployment Audience outcomes A clearer picture of what credible DEI measurement looks like, drawn from Catalyst’s published frameworks A sharper grasp of where bias enters AI systems and what executive teams should be asking about it Direct exposure to a practitioner who has worked with the leadership teams of many of the world’s largest employers on this agenda A more confident vocabulary for senior leaders, particularly men in executive roles, to engage with women’s advancement as a business strategy issue rather than a compliance one

Why organisations work with Andrew Trask He has built the working infrastructure for privacy-preserving AI, not just written about it. PySyft, the open-source framework he created through OpenMined, is used by researchers and engineers to train models on data they never directly see. He sits inside one of the most consequential AI research labs in the world, DeepMind, while also leading an 18,000-strong community of privacy-preserving AI engineers. Few speakers operate credibly in both rooms. His agenda is structured transparency: making it possible for institutions to collaborate on AI without surrendering the underlying data. That is the exact tension a regulated industry leader is now trying to solve. He teaches the material rather than narrates it. Grokking Deep Learning and his Udacity courses have introduced tens of thousands of practitioners to neural networks and to private AI, which is why technical audiences find him credible rather than performative. Biography highlights Senior Research Scientist, Google DeepMind, working on privacy, federated learning, differential privacy, and secure computation. Founder of OpenMined, an open-source community of more than 18,000 researchers and engineers building privacy-preserving AI tools. Creator of PySyft, the open-source framework for training machine learning models on data the model owner cannot see. PhD candidate, University of Oxford, on the Oxford-DeepMind Graduate Scholarship; affiliated with the Future of Humanity Institute and the Centre for Governance of AI. Author of Grokking Deep Learning, Manning Publications, and instructor on Udacity’s Secure and Private AI and Deep Learning Nanodegree courses. Term Member, Council on Foreign Relations. Biography The hardest problem in applied AI is not modelling. It is access. The data that would make a healthcare model genuinely useful sits inside hospital systems that cannot legally share it. The data that would make a financial crime model work is split across banks that compete with each other. The default response has been to do less. Trask has spent the last decade building the technical answer to that problem. Through OpenMined, the open-source community he founded, he created PySyft, a framework that lets engineers train models on data they never directly see. The underlying methods, federated learning, differential privacy, secure multi-party computation, homomorphic encryption, are what serious AI governance now relies on. He calls the broader agenda structured transparency, and it is becoming the operating vocabulary for AI deployment in regulated settings. The institutional positioning matters. He is a Senior Research Scientist at Google DeepMind and a PhD candidate at Oxford, funded by the Oxford-DeepMind Graduate Scholarship and affiliated with the Future of Humanity Institute and the Centre for Governance of AI. He is also a Term Member of the Council on Foreign Relations. That combination puts him inside the frontier AI conversation and inside the AI governance conversation at the same time, which is unusual. The teaching record is the test of whether his ideas travel. Grokking Deep Learning, published by Manning, taught a generation of engineers how neural networks actually work. His Udacity courses on secure and private AI did the same for the privacy-preserving stack. The reason senior technical audiences treat him as a primary source rather than a commentator is that they have already worked through his material. Key speaking topics Privacy-preserving artificial intelligence Federated learning and secure computation AI governance and structured transparency Differential privacy in practice AI safety and responsible deployment The future of data infrastructure for AI Foundations of deep learning for non-specialists Ideal for Chief AI officers, CTOs, and chief data officers in regulated industries (healthcare, financial services, government) deciding how to deploy AI on sensitive data. Boards and audit committees pressure-tested on AI governance, data risk, and the gap between AI ambition and AI infrastructure. Heads of research, innovation, and product engineering teams building the next generation of AI products. Policy and public-sector leaders responsible for AI standards, data sharing, and international AI governance. Audience outcomes A working mental model of the privacy-preserving AI stack, named technique by named technique, instead of the usual abstractions. A clearer view of which AI use cases are unlocked by federated learning and secure computation, and which remain blocked by data access. A grounded read on where AI governance is heading, from someone inside both DeepMind and the Oxford AI governance ecosystem. A direct sense of how to move from AI pilots to deployments that survive regulatory and reputational scrutiny.

Why organisations work with Glen Weyl He is the working bridge between three of the people who matter most in this debate: Vitalik Buterin on Ethereum and Web3, Jaron Lanier on AI and data, and Audrey Tang on civic technology. Senior teams get one room with the network, not three separate conversations. He co-invented Quadratic Voting and Quadratic Funding, mechanisms now used inside crypto ecosystems, civic budgets, and corporate innovation funds. Boards looking at participatory capital allocation are looking at his work, often without knowing it. He led Microsoft’s Office of the CTO work on the OpenAI relationship and now runs Microsoft Research’s Plural Technology Collaboratory. He has seen the inside of how the largest AI partnership in the world is governed, and can talk about it candidly. His book Radical Markets, written with University of Chicago law professor Eric Posner, was named an Economist Book of the Year in 2018 and changed how serious economists discuss property, voting, and antitrust in a digital economy. He works in the same language as policymakers in Taiwan, the EU, and the US Treasury, which makes him unusually useful to organisations whose AI exposure is also a regulatory exposure. Biography highlights Founder and Research Lead, Plural Technology Collaboratory, Microsoft Research. Former Political Economist and Social Technologist, Microsoft Office of the CTO, including the leadership team for the OpenAI relationship. Co-author, Radical Markets, Princeton University Press, 2018; an Economist Book of the Year. Co-author with Audrey Tang of Plurality: The Future of Collaborative Technology and Democracy, 2024. Founder, RadicalxChange Foundation; co-founder and chair, Plurality Institute; co-founder, Harvard GETTING-Plurality Research Network. Named by CoinDesk, WIRED, and Bloomberg Businessweek on their respective lists of most influential people in technology, 2018. Biography Most institutions designed for the industrial economy do not have a good answer to generative AI. Voting systems, ownership rules, antitrust law, and corporate governance were all written for a world where the most powerful entities in a room were human. Glen Weyl’s career has been a sustained attempt to redesign those institutions for a world where they are not. His 2018 book with Eric Posner, Radical Markets, was an Economist Book of the Year and forced a new conversation about property, voting, and antitrust inside serious policy circles. Out of that work came Quadratic Voting and, with Vitalik Buterin, Quadratic Funding. Both are now in operational use in civic budgets and Web3 ecosystems, including projects funded by Ethereum. At Microsoft, he sat inside the Office of the CTO during the period when the company’s relationship with OpenAI became one of the most consequential commercial arrangements in technology. He now runs the Plural Technology Collaboratory, Microsoft Research’s special project on how democratic societies function under generative AI, working with Taiwan’s Audrey Tang, with Harvard, and with civil society groups including the Collective Intelligence Project. His 2024 book with Tang, Plurality, was written openly on GitHub and translated by volunteers into more than a dozen languages, an unusual proof point that the governance ideas in it actually work in practice. For a board trying to decide what AI legitimacy means inside its own organisation, that record makes him one of the few people in the world worth bringing into the room. Key speaking topics Generative AI and democratic institutions Plurality and collaborative technology Quadratic Voting and Quadratic Funding Web3, decentralised identity, and digital ownership Antitrust and platform competition Data as labour and the economics of AI training Ideal for Boards and CEOs setting AI governance and partnership strategy Government, regulator, and central bank audiences on AI and digital policy CTOs and Chief AI Officers working on legitimacy and deployment frameworks Foundations, philanthropic capital allocators, and corporate venture funds rethinking how they fund collective goods Audience outcomes A clearer view of how AI partnerships at the scale of Microsoft and OpenAI are actually governed. A working vocabulary for Quadratic Voting, Quadratic Funding, and Plurality, with concrete examples of where each is operating. A sharper sense of where current antitrust, data, and AI regulation is heading in the US, EU, and Asia. Specific design ideas for participatory decision-making inside large organisations, not generic engagement theory.

Why organisations work with Mo Gawdat His central AI thesis – that these systems reflect the values humans encode into them, and that organisations still have a window to act – was published in 2021 and validated by the subsequent speed of AI deployment. Boards are not getting speculation; they are getting a forecast with a track record. Scary Smart gives senior leadership a specific accountability framework, not a risk briefing: the argument is that the question is not whether AI will be powerful, but what the organisation is actively doing to shape its values now. The Solve for Happy happiness model is a named, reproducible framework developed through the same engineering logic Gawdat applied throughout his technology career – not a wellbeing programme, but a systematic methodology for building psychological stability under pressure. He addresses the external disruption (AI’s structural impact on work and value) and the internal response (the human psychology of navigating it) as a single argument – which is why his sessions land differently in a strategy forum than a conventional AI speaker or a conventional wellbeing speaker would. Seven years inside Google [X] at the point when self-driving cars, Project Loon, and Google Life Sciences were being built and commercialised gives him a credibility baseline that no amount of research or commentary can replicate. Biography highlights Former Chief Business Officer, Google [X] (2013-2018), overseeing commercial strategy for Google’s moonshot innovation division 30-year career in technology spanning IBM, NCR, Microsoft, and Google, including senior roles across emerging markets globally Author of Solve for Happy (Macmillan, 2017), Scary Smart (Macmillan, 2021), That Little Voice in Your Head (Macmillan, 2022), and Unstressable (2024, co-authored with psychologist Alice Law) Scary Smart named a Sunday Times Business Book of the Year (2021) Chief AI Officer at Flight Story, the digital marketing company co-founded by Steven Bartlett Founder of One Billion Happy, a global initiative to share structured approaches to happiness and wellbeing Host of Slo Mo, one of the leading mental health podcasts globally Biography When Scary Smart was published in 2021, its central argument read as speculative: AI would become superintelligent, its real danger lay not in the technology itself but in the values humans encode into it, and organisations still had a narrow window to shape the outcome. Within a year, the release of ChatGPT had reframed the argument as a warning that had arrived early. Mo Gawdat had been inside Google [X] when these systems were being built. Gawdat joined Google in 2007 and served as Chief Business Officer of Google [X] from 2013, overseeing commercial strategy for the moonshot division behind self-driving cars, Project Loon, and Google Life Sciences. His seven years there gave him direct exposure to both the capability and the accountability gaps at the frontier of AI development. He left in 2018 and now serves as Chief AI Officer at Flight Story, the digital marketing company co-founded by Steven Bartlett. The parallel body of work on happiness was not a departure from his technology career. It emerged from the same engineering mindset applied to personal crisis. Following the death of his son Ali in 2014, Gawdat developed the framework at the centre of Solve for Happy: a systematic, reproducible model for well-being grounded in cognitive science. The book became an international bestseller. His thesis is that the two bodies of work are not separate. An organisation that understands the human psychology of its people is better positioned to navigate the disruption AI will accelerate. Unstressable, co-authored with psychologist Alice Law and published in 2024, extends that logic into a practical stress-management framework built around four human systems. He hosts Slo Mo, one of the leading mental health podcasts globally, and his earlier books – That Little Voice in Your Head (2022) and Scary Smart, a Sunday Times Business Book of the Year – continue to reach executive audiences grappling with AI governance and personal resilience across a 30-year technology career. Key speaking topics AI ethics and governance Responsible AI adoption The human impact of AI disruption Happiness science and the engineering of well-being Stress management frameworks Technology leadership and strategic foresight Human values in AI development Ideal for Boards and executive leadership teams making AI governance and adoption decisions Chief People Officers and Chief Technology Officers managing workforce responses to AI disruption Strategy, transformation, and future of work forums where AI risk and human resilience intersect Technology, financial services, and marketing organisations with significant and growing AI exposure Audience outcomes A coherent framework for evaluating AI’s ethical and human risks, grounded in direct experience of building these systems rather than external commentary Clarity on what values organisations need to embed in AI systems now, and why the window to do so meaningfully is narrowing Practical tools from the Solve for Happy model for building psychological stability and resilience under conditions of sustained uncertainty A more calibrated understanding of the timeline and direction of AI development, distinct from both catastrophism and uncritical optimism Practical techniques from Unstressable for identifying and reducing sources of stress at individual and team level

Why organisations work with Ramy Nassar He brings a published, structured method for AI product design from idea to launch, set out in the AI Product Design Handbook and used by enterprise teams who need a repeatable process rather than another inspiration deck. He has run innovation inside Mattel and led design and strategy at Architech for Apple, Air Canada, CIBC, Facebook and Rogers, so the operational reality of shipping new products inside large organisations is in the room. His work separates “AI Now, Next and Never,” giving boards a defensible position on what to deploy, what to wait on, and where to draw governance lines. He teaches design thinking and innovation at McMaster University and Toronto Metropolitan University, and executive programmes at Schulich ExecEd, which keeps the frameworks tested against working leaders. Client engagements span Apple, TD Bank, TELUS, Verizon, New Balance and the Government of Canada, covering both regulated and consumer environments. Biography highlights Author, AI Product Design Handbook Former Head of Innovation, Mattel, where he launched the company’s first innovation lab Former Managing Director, Design and Strategy, Architech Founder, 1000 Days Out, advisory practice on AI and emerging technology Faculty: McMaster University, Toronto Metropolitan University, Schulich ExecEd at York University Featured by CPA Canada at The ONE national conference; speaker at FITC, IxDA, FWD50 and World Usability Congress Biography Most AI projects inside large organisations have the same shape. A pilot ships, attention moves on, and the operating model does not change. Boards then have to decide whether the next round of spend should go into more experiments or into the harder work of getting AI into the product and into the workflow. That is the decision Ramy Nassar is built to inform. The AI Product Design Handbook sets out a repeatable process for taking AI products from idea to launch, with explicit attention to user trust, transparency and governance. It is used by product and design leaders who need a method, not a manifesto. The argument is grounded in his time as Head of Innovation at Mattel, where he launched the company’s first innovation lab and led emerging-technology work for Barbie and Hot Wheels, and earlier as Managing Director of Design and Strategy at Architech, where he ran client work for Apple, Air Canada, CIBC, Facebook and Rogers. Through 1000 Days Out he advises senior teams at Apple, TD Bank, TELUS, Verizon, New Balance and the Government of Canada on AI adoption, strategic foresight and product strategy. His framing of “AI Now, Next and Never” is designed for boards that need to commit capital and set governance lines at the same time, and his strategic foresight work gives leaders a structured way to test decisions against multiple long-range scenarios. Faculty roles at McMaster University, Toronto Metropolitan University and Schulich ExecEd at York University keep the frameworks tested against working executives. CPA Canada featured him at The ONE national conference on turning insights into measurable impact, and his international speaking includes FITC, IxDA, FWD50 and the World Usability Congress. Key speaking topics Artificial intelligence adoption and product design Responsible AI and governance Strategic foresight and scenario planning Innovation strategy Emerging technology and exponential change Digital product and customer experience design Ideal for Boards and C-suite teams setting AI investment and governance policy Chief Product Officers, Chief Design Officers and Chief Innovation Officers moving from pilots to deployed AI Heads of Strategy and corporate development running scenario planning under technology uncertainty Public-sector leaders shaping responsible AI policy and procurement Audience outcomes A defensible “now, next, never” view of where to deploy AI, where to wait, and where to refuse A structured method for taking AI features from concept to launch with governance built in Sharper foresight tools for testing strategy against multiple long-range scenarios Concrete language for communicating AI risk, ethics and product trade-offs to non-technical executives and customers

Why organisations work with Daniel Susskind A rare voice arguing the economics of AI rather than the technology, drawing on academic work at Oxford, King’s College London and the Stanford Digital Economy Lab. Author of two of the most serious books on the subject leaders are now wrestling with: A World Without Work on AI-driven labour displacement, and Growth: A Reckoning on what economic growth itself should be for. Independent recognition from credible bodies. Growth: A Reckoning was runner-up for the Financial Times Business Book of the Year 2024 and selected by Barack Obama among his favourite books of the year. A World Without Work was also an FT Business Book of the Year runner-up. Sits inside the policy conversation, not just the academic one. Member of the UK Government Expert Panel on AI and the Future of Work, with prior roles in the Prime Minister’s Strategy Unit, 10 Downing Street and the Cabinet Office. Speaks directly to the question every professional services firm and large employer is now asking, which is what happens to the work, the workforce and the business model as AI absorbs more of what experts used to be paid for. Biography highlights Mercers’ School Memorial Professor of Business, Gresham College. Research Professor in Economics, King’s College London. Senior Research Associate, Institute for Ethics in AI, Oxford University, and Associate Member of the Oxford Economics Department. Digital Fellow, Stanford Digital Economy Lab. Author of “Growth: A Reckoning” (2024), “A World Without Work” (2020), and co-author of “The Future of the Professions” (2015). Two FT Business Book of the Year runner-up nominations. Member of the UK Government Expert Panel on AI and the Future of Work. Former Prime Minister’s Strategy Unit, 10 Downing Street Policy Unit, and Cabinet Office. Kennedy Scholar at Harvard. Biography The economic question AI poses to boards is not whether it will take jobs. It is which tasks, in which roles, at what pace, and what that does to the wage bill, the talent pipeline and the growth model the business has been built on. Most public discussion stops at the headline. Daniel Susskind’s work starts where the headline ends. “The Future of the Professions”, co-authored with Richard Susskind in 2015, argued that AI would unbundle expert work in law, medicine, accounting and consulting into tasks that machines, paraprofessionals and software would absorb. A decade on, the prediction reads as conservative. “A World Without Work” then took the argument into the wider labour market, asking how societies should distribute income, status and meaning when paid work becomes scarcer for more people. The New York Times called it “required reading for any potential presidential candidate thinking about the economy of the future”. “Growth: A Reckoning”, a Financial Times Business Book of the Year runner-up in 2024 and chosen by Barack Obama as a favourite book of that year, sits behind both. It treats economic growth as a deliberate choice about what societies value, not an inherited assumption. For corporate leaders the relevance is direct. Capital allocation, productivity claims and ESG narratives all rest on growth assumptions that no longer hold without examination. Susskind’s institutional base is unusually broad: Research Professor at King’s College London, Senior Research Associate at Oxford’s Institute for Ethics in AI, Mercers’ School Memorial Professor of Business at Gresham College, and Digital Fellow at the Stanford Digital Economy Lab. He sits on the UK Government Expert Panel on AI and the Future of Work, and previously advised inside the Prime Minister’s Strategy Unit, 10 Downing Street and the Cabinet Office. His TED Talk on the future of work has been viewed more than 1.7 million times. Key speaking topics Artificial intelligence and the future of work The future of the professions Economic growth and its limits Labour market disruption and workforce redesign AI policy and regulation Productivity, automation and the firm Technology, inequality and the social contract Ideal for Boards and executive committees of professional services firms grappling with AI’s impact on the expert business model CHROs and chief people officers planning multi-year workforce design around AI CEOs, CFOs and chief strategy officers debating growth, productivity and capital allocation Government, regulator and public-sector leadership audiences working on AI and labour-market policy Audience outcomes A grounded economic view of how AI changes work, distinct from the consultancy version Sharper questions to put to the firm’s own workforce and productivity assumptions A working frame for distinguishing AI hype from the shifts that will actually hit the P&L A clearer position on what growth means for the business, and where the inherited growth model is breaking Vocabulary and reference points senior teams can use to brief their own boards on AI and workforce strategy

Why organisations work with Maria Ressa She has tested platform governance arguments against actual prosecution, exile threats and a coordinated state-backed disinformation campaign, which gives her a clarity on digital risk that academic experts rarely match. As co-founder of the Real Facebook Oversight Board and co-leader of Columbia’s Technology and Democracy Initiative, she sits at the centre of the policy conversation shaping how governments will regulate platforms and AI. Her Nobel citation specifically named the defence of free expression as a precondition for democracy, giving leadership and ESG audiences a credible voice on information integrity as a governance issue, not a communications one. She runs a working newsroom that has documented platform manipulation in real time, so her arguments come with primary evidence rather than secondary commentary. How to Stand Up to a Dictator gives her a published thesis on the architecture of digital authoritarianism that boards and policy teams can engage with in advance of a session. Biography highlights 2021 Nobel Peace Prize laureate, jointly with Dmitry Muratov, for work safeguarding freedom of expression. Co-founder and CEO of Rappler, the Manila-based investigative news organisation she launched in 2012. Professor of Professional Practice, Columbia University School of International and Public Affairs; Distinguished Fellow and co-leader of the Technology and Democracy Initiative at SIPA’s Institute of Global Politics. Author of How to Stand Up to a Dictator (Harper, 2022), a New York Times bestseller, and Seeds of Terror (2003). 2021 UNESCO Guillermo Cano World Press Freedom Prize; 2018 Golden Pen of Freedom from the World Association of News Publishers. Time Person of the Year 2018; Time 100 Most Influential People; BBC 100 Women. Nearly two decades as CNN bureau chief in Manila and Jakarta; former SVP for News and Current Affairs at ABS-CBN. Biography The 2021 Nobel Peace Prize citation named freedom of expression as a precondition for democracy. It was the first time since 1935 that the prize had been given to working journalists, and the choice was not symbolic. Ressa shared it with Dmitry Muratov for a body of work that treats disinformation, platform power and the erosion of shared reality as the defining governance problem of the decade. Her vantage point is unusual. She co-founded Rappler in Manila in 2012, then ran it through years of state-backed harassment, criminal charges and an online campaign that the company itself documented in forensic detail. That experience produced a working theory of how engagement-driven platforms, weaponised by political actors, dismantle public trust and institutional legitimacy from below. The argument is laid out in How to Stand Up to a Dictator, the Harper book that became a New York Times bestseller and Princeton’s Class of 2027 Pre-read. She now sits at Columbia’s School of International and Public Affairs as a Professor of Professional Practice and co-leads the Technology and Democracy Initiative at the Institute of Global Politics. The role pairs naturally with her work on the Real Facebook Oversight Board, an independent body of journalists, academics and activists holding Meta to account on content governance. Earlier in her career she opened CNN’s Manila bureau, ran its Jakarta bureau through the post-9/11 years, and led news at ABS-CBN; her 2003 book Seeds of Terror remains a reference on Jemaah Islamiyah. For corporate audiences, the value sits in the bridge she builds between platform mechanics and executive decision-making. AI accelerates everything she has been documenting for a decade, and the regulatory response, in Brussels, Washington and Manila, is now arriving in the operating environment of any business with a public-facing reputation. Key speaking topics Disinformation and the integrity of the information ecosystem Platform governance and Big Tech accountability AI ethics and the future of public trust Press freedom as institutional infrastructure Democratic resilience under digital authoritarianism Leadership and moral courage in contested environments Ideal for Boards and C-suite teams reassessing reputational and regulatory risk in an AI-mediated information environment Chief Communications Officers, Chief Risk Officers and General Counsel responsible for platform exposure and disinformation response Public-sector and policy audiences working on technology regulation, democratic resilience and ESG frameworks Leadership programmes seeking a serious voice on values, courage and institutional integrity Audience outcomes A working model of how engagement-driven platforms shape public perception of organisations, leaders and policy. Direct evidence, drawn from Rappler’s own reporting, of how coordinated disinformation campaigns are designed and executed. A clear read on where AI regulation and platform accountability are heading across major jurisdictions. A sharper sense of what leadership looks like when institutional norms are under pressure, told through a Nobel-recognised case. Language and frameworks for treating information integrity as a governance issue at board level, not a communications problem.

Why organisations work with Joe Toscano He left Google over the data practices he saw inside it, then wrote the book on what those practices look like from within. That insider account is hard to replicate at the keynote level. His work translates AI and privacy debates into specific operating decisions: what data to keep, what to delete, what to disclose, and where consent breaks under regulatory scrutiny. As founder of DataGrade and BEACON, he speaks from the position of someone running a privacy-first business, not commenting on one from outside. His public visibility through The Social Dilemma, Fox News, and Forbes means he can hold a non-technical audience on a technical subject without dropping the substance. Biography highlights Featured expert in Netflix’s The Social Dilemma. Author of Automating Humanity (powerHouse Books / Simon & Schuster). Founder and CEO of DataGrade. Founder of the Better Ethics and Consumer Outcomes Network (BEACON). Former Experience Design consultant for Google. TEDx speaker; Forbes contributor; recurring Fox News technology commentator. Biography The companies setting the rules for how consumer data trains AI systems are also the companies whose products most depend on that data. That conflict sits at the centre of Joe Toscano’s work. He came out of Silicon Valley with a designer’s view of how those products are built, then turned that knowledge outward. Toscano was an Experience Design consultant for Google before stepping away in 2017 over what he saw of the industry’s data practices. Automating Humanity, his book with powerHouse Books, set out the argument in detail: how attention is engineered, how disinformation pays, and how automation is being trained on data the public never knowingly handed over. He went on to found DataGrade, a privacy-first data company, and BEACON, a network focused on technology literacy and ethical innovation. The Netflix documentary The Social Dilemma brought that work to a mass audience, and he has since become a regular technology commentator on Fox News and a contributor to Forbes. What makes him useful to boards is the combination of inside knowledge and operating responsibility. He is not theorising about AI governance from a lectern. He is building a company that has to make those decisions every day, and translating that into language a non-technical executive team can act on. Key speaking topics AI ethics and governance Data privacy and consumer trust The business case for privacy-first design Technology literacy for non-technical leaders The future of work under AI and automation Disinformation and platform accountability Regulation and the post-GDPR landscape Ideal for Boards and executive committees setting AI and data governance standards Chief Privacy Officers, CISOs, and Chief Data Officers CMOs and customer experience leaders weighing personalisation against privacy HR and transformation leads planning workforce change driven by AI Audience outcomes A clearer line between defensible and indefensible uses of customer data in AI systems Specific questions a board should be asking about model training data and consent A working view of how privacy can be a commercial advantage, not just a compliance cost Sharper judgement about what to believe and discount in vendor pitches on AI capability

Why organisations work with Miguel Luengo-Oroz He held the inaugural Chief Data Scientist role at the United Nations for six years, applying AI to conflict prevention, refugee response, epidemics and human rights. That is a vantage point no consultant or academic alone can replicate. He runs Spotlab, an operating AI company in clinical diagnostics. His commentary on AI risk is grounded in shipping production systems, not theoretical governance. He has published more than 100 articles in venues including Nature and MIT Technology Review, and has briefed governments in Europe and the United States, including the Global Partnership on AI. He invented MalariaSpot, a crowdsourced game that turned thousands of citizens into diagnostic contributors. He is fluent in both AI ethics doctrine and what it looks like when humans and AI actually share work. Biography highlights First Chief Data Scientist of the United Nations, UN Global Pulse, Executive Office of the Secretary-General, 2016 to 2022. Founder and CEO of Spotlab, an AI platform for clinical research and universal diagnosis. Professor at Universidad Politécnica de Madrid; PhD (special prize) from the same institution; additional MSc from EHESS and École Normale Supérieure, Paris. Obama Foundation Leader (Europe 2023), Ashoka Fellow, MIT Technology Review TR35, Fellow of the Royal Society of Arts, EU Responsible Research and Innovation Award. More than 100 scientific articles, policy briefs and op-eds; featured in Nature, MIT Technology Review, The Guardian and The New York Times. Inventor of MalariaSpot.org, a crowdsourcing video game for malaria diagnosis. Biography The United Nations created its first Chief Data Scientist post in 2016, and Miguel Luengo-Oroz held it for six years. The brief was to put AI and data science to work on problems that do not forgive errors: epidemic response, refugee movements, hate speech detection, conflict prevention, climate. That experience shaped a working philosophy that responsible AI is not a values statement, it is an operating discipline. Today he runs Spotlab, an AI platform for clinical research and diagnostics, built around smartphones, AI models and 3D printing to bring quality diagnostics to diseases largely absent from the digital health economy. He is also a professor at Universidad Politécnica de Madrid, where his research spans generative AI, collective intelligence and systems biology. His commentary draws on more than 100 publications across Nature, MIT Technology Review, The Guardian and The New York Times, and on advisory work with governments in Europe and the United States and the Global Partnership on AI. Recognitions include the Obama Foundation Leaders programme, an Ashoka fellowship, MIT TR35, the EU Responsible Research and Innovation Award, and a fellowship of the Royal Society of Arts. For senior leaders, the value is the combination: someone who has set AI policy inside the most scrutinised public institution in the world, and who currently ships AI products into regulated medical environments. He speaks about AI risk and opportunity with the specifics of someone doing the work. Key speaking topics Responsible and ethical AI AI governance and public-interest technology AI in healthcare and diagnostics AI for sustainable development and humanitarian response Generative AI: applications, risks and limits The future of AI policy and regulation Data science inside multilateral institutions Ideal for Boards and executive committees setting AI governance and risk posture CTOs, Chief Data Officers and Chief AI Officers operationalising responsible AI Healthcare, life sciences and pharma leaders deploying clinical AI Public sector, multilateral and NGO leadership teams using AI in policy and operations Audience outcomes A clear view of where AI risk actually sits in deployment, beyond policy statements Specific examples of AI applied to high-stakes problems inside the UN and in clinical settings A working framework for distinguishing responsible AI as discipline from responsible AI as branding Sharper questions to put to internal AI programmes, vendors and regulators Realistic perspective on what generative AI changes for organisations over the next two to three years

Why organisations work with Hamilton Mann He runs digital and AI transformation at Thales across 68 countries in defence, aerospace, cybersecurity and digital identity, so the advice he gives boards is the advice he himself has to act on inside one of the most regulated operating environments in the world. Artificial Integrity is a published, named framework with a Wiley imprint behind it and a Thinkers50 Distinguished Achievement Award in Digital Thinking. Buyers get a defensible reference point, not a personal opinion. He teaches AI strategy at INSEAD, HEC Paris and EDHEC Business School, which means the content travels at executive education register without being either academic or vendor-coloured. He bridges the two AI conversations boards are stuck between: the engineering question of what the system can do, and the governance question of what the organisation can defend. Most speakers credibly cover one side. Biography highlights Group Vice President, Digital Marketing and Digital Transformation, Thales (defence, aerospace, cybersecurity, digital identity, 68 countries). Author, Artificial Integrity: The Paths to Leading AI Toward a Human-Centered Future (Wiley, October 2024). Thinkers50 Radar 2024 (top 30 emerging business thinkers globally); Thinkers50 Distinguished Achievement Award in Digital Thinking, 2025. Senior Lecturer at INSEAD, HEC Paris and EDHEC Business School; Mentor, MIT Priscilla King Gray Public Service Center. Forbes US contributor on AI; published in Stanford Social Innovation Review, California Management Review, Rotman Management, Knowledge@Wharton, INSEAD Knowledge, I by IMD, Harvard Business Review France. Host of The Hamilton Mann Conversation, a podcast on Digital for Good. Biography The harder problem in enterprise AI is no longer model performance. It is the gap between what a system can do and what an organisation can defend in front of a regulator, a court, a journalist or a customer. Hamilton Mann named that gap and gave it a discipline. His book Artificial Integrity, published by Wiley in October 2024, argues that AI design has spent a decade optimising for intelligence and almost no time on integrity, by which he means systems that demonstrate ethical, moral and social reasoning and remain continuously assessable in that capacity. The argument earned the Thinkers50 Distinguished Achievement Award in Digital Thinking in 2025 and a place on the Thinkers50 Top 10 New Management Books list the same year. The credibility comes from operating reality as much as from publishing record. As Group Vice President for Digital Marketing and Digital Transformation at Thales, Mann runs digital and AI initiatives across 68 countries inside a defence, aerospace, cybersecurity and digital identity business, the kind of environment where a poorly governed AI decision has consequences beyond reputational damage. He carries that lens into his teaching at INSEAD, HEC Paris and EDHEC, his mentoring at MIT’s Priscilla King Gray Public Service Center, and his Forbes US column on AI and society. For a board or executive committee debating AI deployment, the value is concrete. Mann sits at the intersection of three conversations most organisations try to hold separately: the technical, the governance and the strategic. He has a published framework, an operator’s track record and the standing to challenge a leadership team without retreating into either ethics theory or vendor pitch. Key speaking topics Artificial Integrity as an AI design discipline Responsible AI deployment in regulated industries Digital and AI transformation at enterprise scale AI governance for boards and executive committees Digital for Good and the paradoxes of technology Human-centred AI strategy Leadership in the age of AI Ideal for Boards and executive committees setting AI policy and risk appetite Chief AI Officers, CIOs, CTOs and Chief Digital Officers responsible for enterprise deployment Regulated industry leadership in defence, financial services, healthcare, energy and public sector Senior leadership programmes and executive education on AI strategy Audience outcomes A working definition of Artificial Integrity that a leadership team can use to evaluate its own AI portfolio A clearer view of where current AI deployments create defensibility risk and where they create operating advantage The vocabulary and framework to challenge vendors, internal AI proposals and governance gaps with the same standard A reference point grounded in both a published Wiley title and an active operating role at one of Europe’s largest technology groups