AI Ethics & Responsible Technology

Why organisations work with Limor Ziv She closes the gap between AI governance theory and AI commercial performance, with named client work at Google, KPMG, Bright Data, SolarEdge, and Medison Pharma. Humane AI was selected by Meta among 2025’s most promising AI startups; she sits on the Scientific Council of the Israeli Association for Ethics in AI. Her peer-reviewed research with 74 senior AI and data professionals (MDPI, 2025) gives boards a working diagnostic for the breakdowns that destroy AI value, from data and governance to context and business alignment. She works the practitioner seam between academic credibility and commercial deployment, the same person teaches the lecture and runs the workshop afterwards. Operator credibility on the women-in-AI question, with public roles in Israel’s data and ethics communities, without converting that into a separate keynote category. Biography highlights Founder and CEO, Humane AI, selected by Meta among 2025’s most promising AI startups. Postdoctoral fellowship in Human-AI Interaction; Ph.D., Tel Aviv University, where she was named to the “100 Outstanding Lecturers” list. Co-author, “Behind the Algorithm: International Insights into Data-Driven AI Model Development” (MDPI, 2025), based on interviews with 74 senior AI and data professionals. Scientific Council member, Israeli Association for Ethics in AI (IAEAI). Named keynote and consulting work for Google, KPMG, Bright Data, SolarEdge, Medison Pharma, government ministries, and municipalities including Tel Aviv. Biography AI investments are returning less than executive committees expected, and regulatory scrutiny is rising in parallel. The two pressures meet at the same operational layer, where most AI deployments quietly fail. Dr. Limor Ziv built Humane AI to work at that seam. The company was selected by Meta among 2025’s most promising AI startups. In a keynote, she takes apart the hidden risks built into everyday algorithms and gives senior audiences practical ways to govern AI systems and to lower the exposure they create. She works with organisations to capture the upside of AI and avoid the failure modes that come with deploying it. The research underwrites the consulting. Her 2025 paper with Maayan Nakash in MDPI’s Machine Learning and Knowledge Extraction draws on interviews with 74 senior AI and data professionals across countries and sectors. The recurring breakdowns it surfaces are the same ones that destroy commercial performance: weak data quality, missing context, governance gaps, and business misalignment. Her client base spans government ministries and municipalities, universities, and technology companies, including Google, KPMG, Bright Data, SolarEdge, and Medison Pharma. She lectures in graduate programmes at universities and was named to Tel Aviv University’s list of 100 Outstanding Lecturers. The brief is consistent across them: make AI deployments that earn their investment and hold up when someone audits the decisions. Key speaking topics Responsible AI and AI ethics AI risk management and compliance AI governance and regulatory readiness Data quality and data-centric AI Human-AI interaction and human-centred design Realising value from AI investment AI in regulated sectors, including healthcare and finance Operationalising responsible AI in the enterprise Ideal for Boards and executive committees accountable for both the return on AI investment and the defensibility of the AI systems they sign off. Chief AI officers, chief data officers, and CISOs operationalising responsible AI policy while showing it earns its cost. Regulated-industry leadership in healthcare, financial services, and public sector wrestling with AI deployment under compliance pressure. Heads of AI, innovation, and transformation under pressure to show a return on AI spend without creating regulatory exposure. Audience outcomes A working definition of AI risk that distinguishes data risk, model risk, and decision risk, and a sense of where each lives in the organisation. A view of what AI deployment actually demands of operating teams, drawn from her empirical research with 74 senior practitioners across countries and sectors. A grounded read on the live regulatory and ethical debates, from a Scientific Council member of the Israeli Association for Ethics in AI. An honest read on the gap between what AI investments cost and what they return, and on the operating work that decides whether the gap closes.

Why organisations work with Ian Khan He gives executive teams a diagnostic rather than a forecast. The Future Readiness Score, built from his research across hundreds of organisations, turns “are we ready for AI” into a scored view across seven operating pillars. His writing carries commercial weight. Undisrupted won the Bronze Medal at the 2025 North American Book Awards and the Non-Fiction category at the Goody Business Book Awards 2025; Metaverse For Dummies is a Wiley title. He reports on the future as a working journalist, not only a consultant. As executive producer and host of The Futurist on Amazon Prime Video, he has interviewed hundreds of global leaders on the record, which keeps his keynote content closer to evidence than to speculation. He separates AI hype from AI advantage in front of technical and non-technical rooms. His AIRS assessment gives boards a common language for where they sit on vision, use cases, data, governance, and adoption. Biography highlights USA Today bestselling author of Undisrupted, which introduces the Future Readiness Score across seven organisational pillars. Author of Metaverse For Dummies, published by Wiley. Executive producer and host of The Futurist, a streaming series on Amazon Prime Video across more than 45 regions. Director of the documentary Blockchain City and producer of additional films on AI and the future of work. Thinkers50 Future Readiness Award finalist and Thinkers360 Distinguished honoree. Media contributor and on-record commentator featured by CNN and Forbes. Biography Most AI strategy conversations stall at the same point. The executive team agrees the technology matters. Nobody can agree on what to do on Monday. Khan’s contribution is a working answer to that problem, built from research across hundreds of organisations and codified in his book Undisrupted and the Future Readiness Score that sits inside it. The Score moves the question from opinion to diagnostic. It measures an organisation across seven pillars, including engagement, learning, collaboration, culture, innovation, and execution, and returns a prioritised picture of where readiness is thin. His AIRS framework does the equivalent for AI specifically, covering vision, use cases, data, governance, and adoption. Boards use both as a shared map before they approve the next investment. Khan works across the commercial and editorial sides of technology. He is the author of Metaverse For Dummies, published by Wiley, and of additional titles on prompt engineering and value creation. As executive producer and host of The Futurist on Amazon Prime Video, he has interviewed hundreds of founders, scientists, and policy leaders on the record. Commentary work with CNN and Forbes sits alongside that. His keynote practice reflects that dual background. Audiences get a filmmaker’s feel for narrative and a consultant’s insistence on instrumentation, applied to the decisions leadership teams are actually trying to make about AI, automation, and emerging technology. Key speaking topics Artificial intelligence and generative AI strategy Future readiness and organisational diagnostics Digital transformation and enterprise technology adoption Emerging technology and disruption AI governance and responsible deployment Leadership in an AI-driven operating environment Ideal for CEOs, CIOs, and CTOs sponsoring AI strategy across business units Boards and executive committees setting technology investment priorities Transformation and digital leaders responsible for moving pilots into production Government and public-sector leaders assessing AI readiness and governance Audience outcomes A shared vocabulary for assessing where the organisation actually stands on AI and digital readiness. A prioritised view of which technology bets are worth compounding and which to retire. Sharper criteria for AI governance decisions, from data to adoption. Concrete patterns drawn from hundreds of documented executive interviews, not abstract predictions.

Why organisations work with Audrey Tang She has run the experiment that most boards are still debating: AI governance, digital deliberation, and disinformation defence deployed at national scale, with measurable outcomes during a pandemic and a presidential election. She offers a working alternative to the binary of techno-libertarianism and centralised AI control, set out in “Plurality” with E. Glen Weyl and tested inside Taiwan’s government. She built the civic infrastructure she talks about. g0v, the Mask Map, vTaiwan, and Join.gov.tw are operational systems, not concepts, and have been adopted in Japan, the EU, and the United States. Her authority is rare in this category: a TIME100 AI honoree and Foreign Policy Top 100 Global Thinker who has signed off on policy decisions, not just commented on them. Biography highlights First Minister of Digital Affairs of Taiwan, 2022 to 2024; Digital Minister from 2016. Co-author with E. Glen Weyl of “Plurality: The Future of Collaborative Technology and Democracy”. TIME100 Most Influential People in AI, 2023. Foreign Policy Top 100 Global Thinkers, 2019. Co-founder of g0v and architect of Taiwan’s open-data COVID-19 response, including the Mask Map. Ambassador-at-large, University of Oxford Accelerator Fellowship Programme. Biography Most governments responded to COVID-19 with top-down distribution and mandates. Taiwan ran an open-data Mask Map built with civic coders, a participatory platform called vTaiwan, and a disinformation playbook with a 20-minute response window. The minister responsible was Audrey Tang. Tang served as Taiwan’s first Digital Minister from 2016, and as the first Minister of Digital Affairs from 2022 to 2024. Before government, she was a Silicon Valley engineer and a core contributor to Perl and Haskell. She joined the g0v civic-tech community in its early years and helped shape the open-government practices that later became state policy. Her book with E. Glen Weyl, “Plurality: The Future of Collaborative Technology and Democracy”, argues that AI and digital tools can be designed to widen democratic participation rather than narrow it. The book was written openly on GitHub, translated by volunteers into more than a dozen languages, and released into the public domain. It draws directly on what Taiwan built and ran. She has been named to TIME100 AI, Foreign Policy’s Top 100 Global Thinkers, and serves as an ambassador-at-large in the University of Oxford’s Accelerator Fellowship Programme. For a senior audience weighing how to govern AI inside a regulated organisation, she offers something most speakers in this category cannot: a record of decisions made in office, with results visible in pandemic outcomes and election integrity. Key speaking topics Digital democracy and participatory governance AI ethics and trustworthy AI design Plurality and collaborative technology Disinformation defence and election integrity Open-source civic infrastructure Public trust in technology Cybersecurity as democratic resilience Ideal for Boards and executive committees setting AI governance and risk policy Chief Digital, Data, and AI Officers designing deployment frameworks Public-sector and regulated-industry leaders facing trust and legitimacy questions CISOs and risk leads responsible for disinformation, election, or platform integrity Audience outcomes A working mental model for AI governance grounded in a national case, not a thought experiment. A clear view of what participatory and open-source approaches add to organisational decision-making, and where they break. Specific tactics for disinformation response, drawn from Taiwan’s 2-2-2 playbook. A vocabulary for “Plurality” that gives leaders an alternative to the techno-libertarian and centralised-control framings of AI.

Why organisations work with Andrew Ng His AI Transformation Playbook – a named, five-step framework derived directly from building AI teams at Google and Baidu – gives organisations a structured implementation path, not principles. It is the difference between a direction and a plan. He has operated on both sides of the AI adoption challenge: as the person responsible for making two of the world’s largest technology companies into AI-first organisations, and as the founder of platforms that have trained more than 8 million people in AI skills. The failure modes at both ends are not theoretical to him. His “AI is the new electricity” thesis reframes AI as general-purpose infrastructure rather than a feature or a product – a distinction that changes how boards allocate capital and how leadership teams structure accountability. Named to Time’s inaugural Time100 AI list (2023) – recognising active, current influence in the field – and to Amazon’s board of directors. The former signals peer standing; the latter signals boardroom credibility. Through AI Aspire, developed in partnership with Bain & Company, he advises enterprises moving from AI experimentation to scalable transformation – giving organisations access to a perspective tested across venture building, hyperscale operations, and mass education. Biography highlights Co-founded Google Brain – the research team credited with reshaping Google’s approach to artificial intelligence VP and Chief Scientist at Baidu, leading a 1,300-person AI team responsible for the company’s global AI strategy Co-founder and Chairman of Coursera (NYSE: COUR), now serving 150 million+ registered learners globally Founder of DeepLearning.AI – over 8 million people have completed AI courses through his programmes Named to Time100 Most Influential People (2012), Fast Company’s Most Creative People (2014), and Time100 AI (2023) Member of Amazon’s board of directors (appointed April 2024) Author of the AI Transformation Playbook and Machine Learning Yearning, both in wide circulation Holds a BSc from Carnegie Mellon, MSc from MIT, and PhD from UC Berkeley; co-authored over 200 research papers Biography Most AI pilot projects never become AI companies. Andrew Ng has spent years examining why – first as the founding lead of Google Brain and then as VP and Chief Scientist at Baidu, where he built a 1,300-person AI team. The gap between isolated AI experimentation and enterprise-wide capability is the problem he has studied from the inside. His AI Transformation Playbook – drawn directly from that experience – sets out a five-step framework for taking AI adoption from initial momentum to company-wide infrastructure. It circulates widely because it treats AI transformation as an operational challenge, not a technology question. His thesis that AI is infrastructure the way electricity was infrastructure gives boards a strategic frame that holds across industries and business models. Ng co-founded Coursera, which now serves over 150 million registered learners, and founded DeepLearning.AI, through which more than 8 million people have trained in AI skills. Building AI literacy at that scale – and measuring what works – gives him a concrete, tested perspective on what workforce transformation in practice actually requires. Few speakers can point to comparable operational evidence. He holds degrees from Carnegie Mellon, MIT, and UC Berkeley, has co-authored over 200 research papers, and sits on Amazon’s board of directors. Named to Time’s inaugural Time100 AI list in 2023 – recognising current influence rather than historical contribution – he continues to co-found AI companies through AI Fund and advise enterprises on AI strategy through AI Aspire, a firm he built in partnership with Bain & Company. Key speaking topics Enterprise AI adoption and transformation AI strategy for boards and C-suite leaders Agentic AI and the next phase of AI systems AI workforce development and capability building Responsible AI development and regulation Machine learning fundamentals and applied AI The economics of AI as general-purpose infrastructure Ideal for C-suite executives and boards setting AI strategy and capital allocation Chief Technology Officers and Chief Digital Officers leading enterprise AI programmes CHROs and people leaders responsible for AI upskilling and workforce transformation Transformation leads and innovation teams moving from AI pilots to scaled deployment Audience outcomes A structured framework for diagnosing where enterprise AI adoption is stalling and what to do next Clarity on how to build internal AI capability – teams, workflows, and governance – rather than relying on isolated project-by-project approaches A board-level frame for AI as infrastructure, with implications for investment, talent, and competitive positioning Practical understanding of what large-scale AI workforce development requires, drawn from programmes that have trained millions A more grounded view of responsible AI development – distinguishing credible risk from speculative concern – from a practitioner who has argued these positions in public and in policy

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 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 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 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

Key speaking topics Artificial intelligence governance Digital policy and regulation Data strategy and Big Data European AI regulation International technology cooperation Cybersecurity and digital transformation Ideal for Government and public sector leaders Boards and senior executives shaping AI strategy Technology and digital transformation leaders Policy and regulatory audiences Audience outcomes Clear understanding of AI governance frameworks and global policy dynamics Insight into the regulatory landscape shaping artificial intelligence in Europe Practical perspective on aligning AI strategy with public policy requirements Strategic context for navigating digital transformation at national and organisational level Why organisations work with Carme Artigas Direct experience shaping national and European AI policy. Senior leadership background across both public administration and technology ventures. International perspective through United Nations and European institutional roles. Commercial understanding of data and AI from founding and scaling a technology consultancy. Biography Carme Artigas brings rare, first-hand experience of shaping artificial intelligence policy at national, European and international level. As Spain’s Secretary of State for Digitalisation and Artificial Intelligence, she led the country’s digital and AI agenda and represented Spain in key European and global technology forums. During Spain’s Presidency of the Council of the European Union, she coordinated work connected to negotiations on European AI regulation, positioning her at the centre of discussions on responsible AI, governance frameworks and regulatory design. She also serves as Co-Chair of the United Nations High-Level Advisory Body on Artificial Intelligence, contributing to international dialogue on the future of AI governance. Her expertise is grounded in substantial private-sector leadership. She co-founded Synergic Partners, a data analytics and Big Data consultancy that was later integrated into Telefónica, and previously served as CEO of Ericsson Innova, the Ericsson Group’s European venture capital fund. These roles give her a practical understanding of how data strategy, innovation and regulation intersect in real organisations. In addition to her public and corporate leadership, she is affiliated as a Senior Fellow with Harvard Kennedy School’s Belfer Center and is recognised in Spain as an ambassador for Stanford University’s Women in Data Science initiative. For organisations navigating AI adoption, digital transformation and regulatory change, Carme Artigas offers strategic insight drawn from direct experience at the highest levels of technology policy and data-driven business.