Artificial Intelligence & Generative AI

Why organisations work with Brian Solis Operator and analyst in one seat. He runs ServiceNow’s global Innovation and Executive Briefing Centers while writing and researching, so the frameworks he presents are stress-tested on live enterprise engagements. Twenty-plus year track record naming shifts early. His “digital Darwinism” argument, developed across The End of Business as Usual, WTF and X, forecast customer-behaviour-led disruption before most boards were discussing it. Anthropological lens on AI and technology. He frames innovation around how customers and employees are actually behaving, not around the technology stack, which gives CX, marketing and transformation leaders usable material rather than vendor abstractions. Published thesis on the current executive question. Mindshift (Wiley, 2024) sets out how leaders move from reactive management to visionary direction in an AI-first operating environment, making him directly relevant to transformation and CEO agendas right now. Credible with both technology and customer experience audiences. His work is regularly cited across ServiceNow, Salesforce alumni networks, and customer-experience publications, which lets a single booking land with CIO, CMO and CXO communities. Biography highlights Head of Global Innovation, ServiceNow, overseeing Innovation and Executive Briefing Centers in Silicon Valley, New York, London, Paris, Sydney and Singapore. Former Global Innovation Evangelist, Salesforce. Former Principal Analyst, Altimeter Group, covering digital transformation, customer experience and disruption. Author of eight business books including Mindshift (Wiley, 2024), Lifescale (Wiley, 2019), X: The Experience When Business Meets Design, What’s the Future of Business and The End of Business as Usual. Ranked in Thinkers360 Top 50 Metaverse Thought Leaders, 2023. Hosts the (r)evolution video series and the WTF podcast, with a combined following of more than 700,000 across social platforms. Biography Digital transformation has been oversold and under-delivered inside most large enterprises. Programmes launch, dashboards light up, and the underlying operating model stays the same. Brian Solis has been writing about this gap for two decades and now sits inside it, as Head of Global Innovation at ServiceNow, running Innovation and Executive Briefing Centers across Silicon Valley, New York, London, Paris, Sydney and Singapore. His argument across eight books is consistent. Customer and employee behaviour shifts first, technology amplifies the shift, and organisations that treat innovation as a theatre of announcements get outrun by the ones that rewire how decisions are made. He captured this as “digital Darwinism” in The End of Business as Usual and sharpened it in X: The Experience When Business Meets Design and What’s the Future of Business. Mindshift, published by Wiley in October 2024, reframes the same question for an AI-first environment. It is aimed at executives who need to move their teams from reactive management to a visionary posture, spot trends early and convert them into prioritised innovation bets. Before ServiceNow, Solis was Global Innovation Evangelist at Salesforce and, before that, Principal Analyst at Altimeter Group, where he built much of the public research base he still draws on. He is one of the few voices in this space who operates at the intersection a senior buyer actually cares about: the analyst who names the shift, the author who frames it for a boardroom, and the operator responsible for making it real inside a global enterprise. Key speaking topics Digital transformation and digital Darwinism AI-era leadership and the mindshift from reactive to visionary Innovation strategy and the future of the enterprise Customer experience and behavioural change Disruption and emerging technology trends The future of work and employee experience Ideal for CEO, CIO, CDO and transformation leads responsible for enterprise-wide digital and AI strategy. CMO, Chief Customer Officer and CX leads rebuilding the customer model around new behaviour. Innovation, R&D and strategy leaders moving from proof-of-concept to operating-model change. Board and executive offsites framing the next three to five year technology and experience agenda. Audience outcomes A sharper read on which behavioural and technology shifts are material for their sector right now. A working definition of the difference between innovation theatre and innovation that changes the operating model. Language to argue internally for a move from reactive programmes to a visionary, trend-led agenda. A framework from Mindshift for spotting, prioritising and acting on emerging opportunities in an AI-first environment. Specific cues for aligning customer experience, employee experience and technology investment around the same thesis.

Why organisations work with Brent Hoberman He has built and exited two unicorns, lastminute.com and Made.com, and can speak to scaling and to failure with equal credit. Through Founders Factory and firstminute capital, he has first-hand visibility of more than 400 early-stage companies and 12 seed-stage unicorns, giving corporate audiences a live read on where technology is moving. His corporate partner list at Founders Factory, including The Guardian, L’Oreal, easyJet, Aviva and Reckitt Benckiser, means he speaks the language of incumbent strategy as well as founder strategy. As Co-Chair of Enterprise Britain and an adviser to successive UK Prime Ministers, he frames growth inside the real policy and capital conditions leaders operate under. He is candid about what went wrong at Made.com, which gives senior audiences a working case study in IPO timing, governance and post-pandemic demand rather than a highlight reel. Biography highlights Co-founder and former CEO of lastminute.com; sold to Sabre for approximately $1.1bn in 2005. Co-founder of Made.com; founding chairman until shortly before its 2021 IPO. Co-founder and Executive Chairman of Founders Factory, Founders Forum and firstminute capital. Appointed CBE in the 2015 New Year Honours for services to entrepreneurship. Co-Chair of Enterprise Britain; has advised multiple UK Prime Ministers on entrepreneurship policy. Non-executive director roles have included Guardian Media Group, TalkTalk, Shazam, Time Out and The Economist. Biography Lastminute.com went public in March 2000, weeks before the dot-com market broke. The IPO was 43 times oversubscribed and remains one of the fastest company listings in European history. Brent Hoberman was its co-founder and CEO, and he ran the business through the crash and on to a $1.1bn sale to Sabre in 2005. That arc, from frenzy to survival to exit, sits under almost everything he says on stage. Since then he has built three platforms that back other founders. Founders Factory runs corporate-backed accelerators with partners including The Guardian, L’Oreal, easyJet, Aviva, Marks and Spencer and Reckitt Benckiser. firstminute capital is a global seed fund backed by more than 130 unicorn founders. Founders Forum is the community that connects the two. The combined portfolio gives him a working view across several hundred early-stage technology companies at once. He also co-founded Made.com in 2010 and was its founding chairman. He stepped down before the 2021 IPO, having questioned its timing, and the company later entered administration. He uses that outcome directly in corporate sessions on governance, category demand and IPO readiness, which is rare among founders at his level. Outside operating roles, he co-chairs Enterprise Britain with Stephen Fitzpatrick and has advised successive UK Prime Ministers on small business, scale-up and entrepreneurship policy. He was appointed CBE in 2015 for services to entrepreneurship. The policy work matters on the platform because it lets him connect founder behaviour, capital markets and government posture in a way most technology speakers cannot. Key speaking topics Entrepreneurship and founder psychology Scaling consumer internet and marketplace businesses Venture investing and early-stage capital Corporate innovation and startup partnerships AI and consumer technology trends UK and European tech policy Ideal for Boards and executive committees reviewing innovation strategy Corporate venture and M and A teams working with startups CEO and founder gatherings inside private equity and VC portfolios Senior leadership offsites at consumer, retail, media and financial services firms Audience outcomes A clear read on which early-stage technology categories are attracting serious capital and why A practical view of how corporates get useful work out of startup partnerships, from someone who structures them Frank lessons from a founder who has been through a record-breaking IPO, a billion-dollar exit and a public company collapse A sharper sense of how UK and European policy, capital and talent conditions shape what boards can realistically plan for

Why organisations work with Brad Templeton He has sat inside the Google self-driving car program as a strategy and technology consultant since 2010, giving him a read on the robotaxi industry that armchair analysts cannot match. He holds 21 patents across self-driving cars and telephony, so claims about what is technically possible come from someone who has actually built in the space. As founder of ClariNet in 1989, the first company built to do commercial business on the internet, he has a forty-year pattern of calling commercial shifts before the market sees them. Twenty years on the board of the Electronic Frontier Foundation, including a decade as Chairman, means he speaks credibly on the privacy, surveillance and civil-liberties consequences of AI and autonomy. He is a founding faculty member and Chair for Computing and Networks at Singularity University, where the brief is to frame exponential technology change for senior decision-makers. Biography highlights Founder and CEO of ClariNet Communications (1989), the first company established to conduct commercial activity over the internet. Chairman Emeritus of the Electronic Frontier Foundation, Chairman from 2000 to 2010, board member since 1997. Founding faculty and Chair for Computing and Networks at Singularity University since 2009. Strategy and technology consultant on the Google self-driving car project, now Waymo, since 2010. Inventor on 21 patents in autonomous vehicles and telephony. Forbes contributor on robocars; publisher of Robocars.com and the long-running Brad Ideas blog. Board member of the Foresight Institute; plaintiff in Reno v. ACLU. Biography ClariNet went live in June 1989 and sold the first commercial subscription on the internet to Stanford University. The founder was Brad Templeton. That single contract is the practical birth of the dot-com economy, and it sets the pattern for the rest of his career: spotting the commercial shape of a technology before the market has language for it. Two decades later the same instinct took him into Google’s self-driving car program. Since 2010 he has consulted on strategy and technology for what is now Waymo, while also writing a reference column on the industry for Forbes and at Robocars.com. His 21 patents in autonomous vehicles and telephony make the commentary load-bearing; he is not narrating the robotaxi race from the outside. Alongside the commercial work, Templeton spent twenty years on the board of the Electronic Frontier Foundation, a decade of that as Chairman, and was a named plaintiff in Reno v. ACLU, the Supreme Court case that struck down the Communications Decency Act. That record is why boards bring him in when the question shifts from “does the AI work” to “what fights over privacy, surveillance and liability will shape who gets to deploy it.” At Singularity University, where he has been Chair for Computing and Networks since the founding faculty, the job is translating exponential technology curves for executives who need to plan against them. Few speakers combine an operator record in autonomous vehicles, a founder’s claim on the commercial internet, and two decades of civil-liberties advocacy in the same briefing. Key speaking topics Autonomous vehicles and the robotaxi industry Exponential technology and Moore’s Law thinking Artificial intelligence deployment and strategy Privacy, surveillance and civil liberties in a connected economy Internet history and the pattern of commercial technology shifts Future of mobility and urban transportation Cybersecurity and technology policy Ideal for Boards and executive teams sizing investment or partnership decisions in autonomous vehicles, mobility or AI. CTOs and chief innovation officers testing internal assumptions about exponential technology timelines. General counsel, chief privacy officers and policy leads working through AI and surveillance exposure. Automotive, insurance, logistics and urban-planning leadership teams preparing for autonomous deployment. Audience outcomes A sharper read on which autonomous-vehicle timelines are grounded and which are vendor marketing. A working mental model for exponential technology curves and what they mean for planning horizons. Specific case material from inside the Google and Waymo programs that is hard to source elsewhere. A clearer view of the privacy, liability and civil-liberties questions that will shape AI and autonomy regulation. Named examples drawn from forty years of commercial internet history, used to pressure-test current assumptions.

Why organisations work with Bernard Marr His frameworks for data strategy and AI adoption are grounded in peer-reviewed academic research from Cambridge and Cranfield – which means they hold up to internal scrutiny in ways that practitioner opinion rarely does. Business Trends in Practice, winner of the 2022 Business Book of the Year Award, gives executive audiences a shared, structured vocabulary for decisions that are otherwise made in fragmented, jargon-heavy conversations. His Forbes column reaches approximately one million readers a month – meaning his conceptual framing is often already in the room before he arrives, which accelerates rather than starts the conversation. He advises organisations across the full spectrum of sectors – from Google and Microsoft to the Bank of England, NATO and the NHS – which gives him a pattern-recognition advantage that single-sector specialists cannot replicate. Where most AI speakers address technology adoption as an IT problem, Marr consistently frames it as a governance and leadership problem – which is what boards and C-suites are actually wrestling with. Biography highlights Research Fellow, Cambridge Judge Business School; subsequently at Cranfield School of Management – before founding Bernard Marr & Co in 2006 Author of more than 20 books on AI, data strategy and digital transformation, published in over 20 languages Business Trends in Practice named Business Book of the Year 2022; additional awards include the CMI Management Book of the Year, Axiom Book Award and WHSmith Best Business Book Award Ranked by LinkedIn as one of the top 5 business influencers in the world Regular contributor to Forbes and the World Economic Forum; media presence includes BBC News, Sky News, the Financial Times, Wall Street Journal and HBR Advisory clients include Amazon, Google, Microsoft, the Bank of England, NATO, the NHS, Shell and the United Nations Biography Bernard Marr spent his early career as a research fellow at Cambridge Judge Business School and then at Cranfield School of Management, where his published work – cited more than 5,400 times – focused on business performance, intellectual capital and strategic measurement. In 2006 he left academia to found Bernard Marr & Co, taking that analytical infrastructure into advisory work with some of the world’s most complex organisations. His books – more than twenty of them, translated into over twenty languages – are not airport business books. Data Strategy, AI Strategy, Generative AI in Practice and Future Skills each address a specific executive decision: how to treat data as a governed asset, how to build an AI adoption roadmap, how to prepare a workforce for automation. Business Trends in Practice won the 2022 Business Book of the Year Award. His writing for Forbes, published at a rate of around three articles per week, gives those frameworks sustained reach into executive audiences between engagements. What makes Marr useful to a board is not that he explains technology well – many speakers do that. It is that he consistently reframes technology questions as governance questions: who owns the data strategy, how do we assess AI risk, what does leadership fluency in this area actually require? These are the questions that stall transformation programmes, and they sit above the pay grade of a CTO. His advisory work spans Google, Microsoft, Amazon, the Bank of England, NATO, the NHS, Shell and the United Nations – a range that gives him cross-sector pattern recognition that sector-specific specialists cannot replicate. The organisations that benefit most from his work are those where the executive team is technically literate enough to know they don’t know enough, and needs a structured way to close that gap. Key speaking topics AI strategy and adoption for executive leadership Data strategy and data governance Generative AI and its organisational implications Digital transformation and business performance Future of work and future skills Emerging technology trends and business impact Strategic performance management Ideal for C-suite and board-level audiences navigating AI and data investment decisions Chief Digital Officers, Chief Data Officers and technology transformation leads Senior leadership teams ahead of major digital transformation programmes Corporate and enterprise conference audiences requiring clarity on technology without technical fluency as a prerequisite Audience outcomes A working framework for evaluating AI and data investments – not just a description of what they are Clearer language for discussing technology strategy at board level, with less dependence on specialist intermediaries Understanding of which emerging technology trends carry genuine near-term organisational implications versus which are still speculative A more structured approach to data governance and the conditions under which data generates strategic advantage Insight into the skills and capabilities organisations will need to build – and which to acquire versus develop internally

Why organisations work with Avinash Kaushik He built the intellectual vocabulary a generation of marketers now uses, including the See-Think-Do-Care framework that maps content, media and measurement to real customer intent. Sixteen years as Google’s Digital Marketing Evangelist gave him a view of marketing performance across most of the world’s largest advertisers, not a single case study. He bridges analytics and brand in a room that usually forces leaders to pick one, advising both a measurement firm (Human Made Machine) and a global fashion group (Tapestry). His books sit on the desks of working practitioners in ten-plus languages; the argument has survived translation, platform change and the rise of generative AI. He is unusually direct about what does not work in marketing measurement, which is why senior buyers use him to sharpen internal debates rather than flatter them. Biography highlights Former Senior Director of Global Analytics and Digital Marketing Evangelist at Google, a sixteen-year tenure. Global Chief Strategy Officer at Human Made Machine; Brand Strategy and Marketing Transformation Consultant at Tapestry. Author of “Web Analytics: An Hour a Day” and “Web Analytics 2.0” (Wiley), translated into more than ten languages. Originator of the See-Think-Do-Care framework for intent-based marketing strategy. Recipient of the American Statistical Association’s Statistical Advocate of the Year and the Web Analytics Association’s Most Influential Industry Contributor award. Writes “The Marketing Analytics Intersect” newsletter, read by approximately 55,000 marketing and analytics leaders. Biography Marketing leaders rarely struggle for data. They struggle to decide what any of it means for growth next quarter. That is the problem Avinash Kaushik has spent two decades making tractable, first inside Google as its Senior Director of Global Analytics and Digital Marketing Evangelist, and now as global Chief Strategy Officer at Human Made Machine and brand strategy consultant to Tapestry. His See-Think-Do-Care framework reframed digital marketing around customer intent rather than channel or demographic, and it is now embedded in the working language of marketing teams from consumer goods to financial services. It is a simple idea with a disciplined consequence: measurement and content have to follow the audience’s state of mind, not the agency’s media plan. Two books, “Web Analytics: An Hour a Day” and “Web Analytics 2.0”, carried that argument into practice and have been translated into more than ten languages. The American Statistical Association named him Statistical Advocate of the Year; the Web Analytics Association recognised him as its Most Influential Industry Contributor. He has taught and advised at Stanford, USC Annenberg and the Rotman school at Toronto. What sets his current work apart is the refusal to treat AI as a separate topic. In rooms with CMOs and CFOs, he draws the line from intent-based customer understanding to incrementality-based measurement to where generative AI actually earns its keep. The recommendation is usually sharper and the vendor pitch usually weaker by the time he is done. Key speaking topics Intent-centric marketing strategy Incrementality-based marketing measurement AI and generative AI in marketing Digital analytics and data-driven decision making Customer-centric growth and retention Marketing transformation for senior leaders The See-Think-Do-Care framework in practice Ideal for CMOs and marketing leadership teams rebuilding measurement for an AI-first environment. Boards and executive teams stress-testing the commercial return from digital and marketing investment. Heads of analytics, data and performance marketing aligning with brand and commercial functions. CEO and CFO audiences who want a serious outside view on marketing’s contribution to growth. Audience outcomes A clearer line between customer intent, marketing activity and commercial outcome. A sharper test for whether a measurement approach is actually incremental or just reported. A working critique of how generative AI is being sold into marketing and where it earns real return. A shared vocabulary, grounded in See-Think-Do-Care, that senior teams can use to align content, media and measurement. A more confident internal argument about where to stop investing, not only where to invest more.

Why organisations work with Arun Sundararajan He works inside the regulatory machinery his audiences are exposed to. Testimony to the US Congress, the European Parliament and the United Nations, plus a seat on the World Economic Forum’s AI Governance Alliance, means he can tell a board where AI rules are actually heading, not where the press thinks they are. His research asks a question most AI strategies skip: what part of “human capital” should remain owned by humans once a model has learned it. For any company building on or competing with generative AI, that question sits underneath copyright exposure, talent contracts and product liability at the same time. He separates durable economic shifts from cycle noise. The same economist who mapped the move to crowd-based capitalism in The Sharing Economy now tells executives which AI effects are structural and which are hype, a distinction worth real money in capital allocation. He advises both sides. He works with technology companies on strategy, litigation and regulation, and with non-tech boards on AI governance and foresight, so he understands the incentives of the firms building the infrastructure your business now depends on. Biography highlights Harold Price Professor of Entrepreneurship at NYU Stern and Director of its Fubon Center for Technology, Business and Innovation. Author of The Sharing Economy (MIT Press, 2016), winner of the Axiom Best Business Books Award and translated into five languages. Has given testimony on the digital economy and AI to the US Congress, the European Parliament and the United Nations. Member of the World Economic Forum’s AI Governance Alliance; former member of the Carnegie Council’s AI and Equality Initiative. Recognised with a Thinkers50 Radar Thinker Award, nine academic Best Paper awards and two Google Faculty Awards. Author of more than 40 op-eds across the New York Times, Financial Times, Guardian, Wired, Le Monde and Harvard Business Review, and a regular AI commentator for CNN, CNBC and Wired. Biography Generative AI learns to write, compose and design by training on work that people already made. That creates a problem older intellectual property law was never built for: a person’s past output is now also the blueprint for a machine that can reproduce their skill. Arun Sundararajan has made this the centre of his work, framing it as a single question for policymakers and boards: what facets of human capital should be owned by humans? The question carries weight because of where he asks it. As an economist at NYU Stern, Director of its Fubon Center for Technology, Business and Innovation, and a member of the World Economic Forum’s AI Governance Alliance, he has given testimony to the US Congress, the European Parliament and the United Nations. His paper “Rethinking Intellectual Property Law in an Era of Generative AI” lays out why copyright designed for the internet era misfires when the thing being copied is a creative process rather than a file. His authority on technological transitions is established. The Sharing Economy, published by MIT Press, was the early rigorous account of platforms like Uber and Airbnb displacing the managed corporation, and it won the Axiom Best Business Books Award. That track record matters now because the same economist is telling executives which AI effects are structural and which are noise, a judgment his recent work on the AI-capital-to-labour threshold makes concrete. What distinguishes him from the wider future-of-work field is the second half of his argument. Alongside the ownership question, he presses the case for national infrastructure that lets people move between occupations mid-career with dignity, treating workforce displacement as a design choice rather than an inevitability. For a board weighing how far to build on generative AI, he is the rare voice who can map both the legal claims forming underneath the technology and the economic settlement that will determine whether it holds. Key speaking topics AI governance and regulation Intellectual property and copyright in the age of generative AI Ownership of human capital The AI-driven future of work Platform strategy and network effects Antitrust and market power in technology Ideal for Boards and C-suites setting generative AI strategy, particularly where IP exposure, talent contracts or litigation risk are in play. Chief Legal Officers, General Counsel and Chief Strategy Officers navigating AI regulation across US, EU and Asian jurisdictions. Policymakers and regulators shaping AI, copyright and labour rules. Technology and platform companies setting strategy against a shifting governance backdrop. Audience outcomes A clear read on where AI regulation is actually heading across the major jurisdictions, from someone inside the bodies writing it. The ability to tell which AI effects on their industry are structural and which are cycle-driven hype. A sharper view of their company’s exposure on IP, copyright and the ownership of human capability. A framework for workforce planning that treats AI-driven displacement as something to design for, not absorb passively.

Why organisations work with Andrew McAfee His Geek Way framework – four named cultural norms (science, ownership, speed, openness) derived from evolutionary biology and management research – gives leadership teams a specific, testable diagnostic for why their organisations underperform digitally, not another instruction to move faster or fail more His research at MIT’s Initiative on the Digital Economy produces evidence-based findings on how AI and automation are actually affecting productivity and competitive structure – drawn from organisations that have already made the transition, not from modelled projections He holds simultaneous positions as MIT Principal Research Scientist, inaugural Visiting Fellow at Google’s Technology and Society group, and co-founder of Workhelix, an AI workforce optimisation startup – a combination that grounds his analysis in research, platform-scale practice, and operating reality at once The Second Machine Age and Machine, Platform, Crowd – both New York Times bestsellers co-authored with Erik Brynjolfsson – established the intellectual framework through which most serious organisations now think about automation, labour displacement, and platform competition; many executives in the room will be updating assumptions formed by those books He and Brynjolfsson are the only individuals named to both the Thinkers50 ranking of the world’s top management thinkers and the Politico 50 group of people transforming American politics – a dual recognition that reflects the reach of his work into the policy questions, not just the business questions, that will define the digital economy’s next decade Biography highlights Principal Research Scientist, MIT Sloan School of Management; co-founder and co-director, MIT Initiative on the Digital Economy Inaugural Visiting Fellow, Technology and Society, Google Co-founder, Workhelix (AI workforce optimisation startup) Six-time Thinkers50 honoree; Thinkers50 Digital Thinking Award 2015 with Erik Brynjolfsson; one of only two individuals named to both the Thinkers50 and the Politico 50 Author of The Geek Way (Economist Best Books 2023; Forbes Top 10 Business Books 2023) and More from Less; co-author of The Second Machine Age and Machine, Platform, Crowd (New York Times and Wall Street Journal bestsellers) Contributor to Foreign Affairs, Harvard Business Review, The Economist, The Wall Street Journal, and The New York Times; featured on CNN, 60 Minutes, TED, and the World Economic Forum Biography The gap between digital investment and digital performance is one of the most consequential – and least clearly explained – problems in business strategy. Andrew McAfee, Principal Research Scientist at MIT’s Sloan School of Management and co-founder of MIT’s Initiative on the Digital Economy, has spent three decades building the research base to explain it precisely. His 2023 book The Geek Way – named a best book of the year by both The Economist and Forbes – makes a specific argument: the companies consistently outperforming their sectors share four cultural norms (science, ownership, speed, openness), and those norms are not accidents of Silicon Valley geography but replicable patterns grounded in evolutionary science. Organisations that treat digital transformation as an infrastructure challenge, McAfee argues, are misidentifying the problem. The bottleneck is almost always managerial culture, not technology capability. That argument carries weight from multiple directions. McAfee is the inaugural Visiting Fellow at Google’s Technology and Society group and co-founder of Workhelix, an AI startup focused on workforce optimisation – positions that situate his MIT research in both platform-scale and operating practice. His earlier books with Erik Brynjolfsson – The Second Machine Age and Machine, Platform, Crowd, both New York Times bestsellers – established the frameworks that shaped how most serious organisations now think about automation, platform competition, and the economics of digital productivity. He and Brynjolfsson are the only individuals named to both the Thinkers50 ranking of the world’s top management thinkers and the Politico 50 group of people transforming American politics – a pairing that reflects how far McAfee’s work extends beyond corporate boardrooms into the policy questions about AI, labour, and economic growth that will define the decade ahead. Key speaking topics AI and digital business performance The Geek Way: cultural norms for the digital organisation Platform competition and digital business models Technology, productivity, and economic growth Machine intelligence and the future of work Dematerialisation and sustainable growth Organisational culture in the technology-driven enterprise Ideal for C-suite and board audiences evaluating digital strategy and competitive positioning against digital-native rivals Strategy and transformation leads in established industries under sustained digital disruption Innovation and R&D leaders benchmarking organisational culture against technology-sector performance models Executive education programmes on digital leadership, AI adoption, and future-of-work strategy Audience outcomes A clear account of why digital-native organisations outperform incumbents structurally – not through superior technology budgets but through specific, replicable management norms A practical diagnostic framework (The Geek Way: science, ownership, speed, openness) for identifying where organisational culture is constraining digital performance Evidence-based perspective on how AI and automation are actually affecting productivity and workforce structure, grounded in MIT research rather than market projections A more disciplined vocabulary for separating genuine digital transformation from technology investment that changes operating performance little Sharper thinking on platform competition and the long-term viability of traditional business models against digital-native challengers

Why organisations work with Andrew Hessel He is one of a small group of people actually running a human-genome-scale project. Co-founding Genome Project-write with George Church and Jef Boeke gives him a direct line of sight into what will be technically and commercially real in the next ten years, not a commentator’s view. He has built companies in this space, not just written about it. Miikana Therapeutics, Pink Army Cooperative and Humane Genomics each tested a different commercial model for synthetic biology, which is what boards want when they are sizing their own exposure. His Autodesk work made the abstract concrete. The phiX174 genome his team synthesised sits in the Museum of Modern Art’s collection, which is a useful anchor for a room that has not yet understood that genomes can be printed. The Genesis Machine, co-authored with Amy Webb, gives leadership teams a shared reference point. It was named a New Yorker Best Book of 2022 and is already on the reading lists of strategy and R and D functions thinking through biotech platform bets. He speaks to risk as fluently as opportunity. Biosecurity, governance and dual-use are part of his core argument, which matters for regulated industries and for any board that has to sign off on a biology-forward strategy. Biography highlights Co-founder, Genome Project-write (GP-write), the international effort to engineer large genomes including the human genome, launched in 2016 with George Church, Jef Boeke and Nancy J. Kelley. Co-founder and President, Humane Genomics, a synthetic-virus cancer therapeutics company based in New York. Distinguished Researcher, Autodesk Bio/Nano Programmable Matter group, 2012 to 2018; led the synthesis of bacteriophage phiX174, a print of which entered the Museum of Modern Art’s collection. Founding faculty and former co-chair of Bioinformatics and Biotechnology, Singularity University. Co-author with Amy Webb of The Genesis Machine: Our Quest to Rewrite Life in the Age of Synthetic Biology (PublicAffairs, 2022), a New Yorker Best Book of 2022. AAAS-Lemelson Invention Ambassador, 2015; contributor to Scientific American. Biography Genome Project-write launched in 2016 with a plan to engineer genomes at the scale of the human genome. Hessel co-founded it with Harvard geneticist George Church, NYU’s Jef Boeke, and Nancy J. Kelley, after a period advocating that biology needed an equivalent to the software industry’s write phase, not just the read phase delivered by the original Human Genome Project. That framing runs through his career. As Distinguished Researcher at Autodesk from 2012 to 2018, he led the team that designed and printed the bacteriophage phiX174 genome in three weeks for roughly a thousand dollars, a demonstration that biology had become a design discipline. A copy of that print entered the collection of the Museum of Modern Art. Before Autodesk he was founding faculty at Singularity University, where he built and co-chaired the Bioinformatics and Biotechnology track. He is also an operator. He co-founded Miikana Therapeutics in 2002, launched Pink Army Cooperative in 2009 as an open-source biotech experiment in personalised cancer therapy, and co-founded Humane Genomics in 2017 to develop synthetic oncolytic viruses, starting with a veterinary indication before moving to human oncology. Each company is a different bet on how synthetic biology gets to market. His 2022 book with futurist Amy Webb, The Genesis Machine, is the clearest articulation of his argument: synthetic biology is on the same kind of curve that digital computing was in the 1970s, with the same mix of platform opportunities and governance risks. The book was named a New Yorker Best Book of 2022 and is widely used by strategy teams trying to build a common vocabulary for biotech decisions. He was named an AAAS-Lemelson Invention Ambassador in 2015 and contributes to Scientific American. Key speaking topics Synthetic biology and the future of medicine Programmable genomes and the write phase of biotechnology Biosecurity and governance of engineering biology Personalised and precision cancer therapies Platform economics of bioengineering Convergence of AI, software and biology Ideal for Pharma, biotech and medtech boards sizing long-horizon platform bets CTOs, Chief Scientific Officers and heads of R and D in regulated industries Insurance, agriculture, food and materials leaders exposed to biological innovation Strategy and foresight teams building scenarios for the next decade of life sciences Audience outcomes A working model of synthetic biology as an industrial platform, not a research topic A clearer read on which biology-driven shifts are near-term commercial and which are still speculative Named examples of where programmable biology is already changing medicine, agriculture and materials A sharper view of the biosecurity and governance questions that sit alongside the commercial upside Language and reference points leadership teams can use to brief their own boards

Why organisations work with Andrew Grill He gives leadership teams a working vocabulary for AI, quantum, blockchain, and adjacent technologies, built on the 200+ concepts codified in “Digitally Curious” and tested on boards at Vodafone, Dell, Nestle, and the NHS. His engineering training and former IBM Global Managing Partner role mean technical claims hold up under scrutiny from a CTO, while the framing stays legible to a CFO or CHRO. Each session ends with the “Curious Five”, a concrete set of follow-up actions, so the room leaves with decisions to make rather than slides to forward. He has delivered five TEDx talks and advises at board level, so the same material scales from a 1,500-person keynote to a closed strategy session. Biography highlights Former Global Managing Partner, IBM Social Consulting Author, “Digitally Curious” (Wiley, 2024), international bestseller Host, the Digitally Curious Podcast, running since 2019 Named to the AI 100 UK List 2025 for responsible AI leadership Five TEDx talks delivered in London and Cardiff Non-Executive Director, Britain Australia Society Bachelor of Electronic Engineering plus two Master’s degrees (Engineering, MBA) Biography Every board now has AI on its agenda. Far fewer have a clear view of which decisions inside the business actually change because of it. Andrew Grill built his career in the gap between those two positions, first as a telecoms engineer at Optus and Telstra in Australia, then as Global Managing Partner in IBM’s Social Consulting practice, working with some of the largest enterprises in the world on how technology reshapes the way they operate. “Digitally Curious”, published by Wiley in 2024, is the distilled version of that experience. It walks executives through more than 200 technology concepts, from generative AI and quantum to blockchain and 5G, and ends every chapter with the Curious Five, a short set of concrete actions. The book reached international bestseller status and has become the spine of his keynote and advisory work. The podcast of the same name, running since 2019 with more than 60 interviews, gives him a working library of case material. That shows up in the room. Boards at Vodafone, Dell, Nestle, DHL, Sanofi, Bupa, and the NHS have brought him in for sessions that move from technology explanation to specific organisational choices, usually in the same hour. He has delivered five TEDx talks across London and Cardiff, appears regularly on BBC, Sky News, Channel 4, and in The Economist and Financial Times, and was named to the AI 100 UK List in 2025 for his work on responsible AI. The throughline is consistent: make the technology legible to the people who actually have to decide what to do about it. Key speaking topics Artificial intelligence and generative AI for business Digital transformation at board level Responsible AI and AI governance The future of work Emerging technology: quantum, blockchain, Web3 Customer experience in an AI-mediated economy Digital fluency for senior leaders Ideal for Boards and executive committees sequencing their AI strategy CIOs, CDOs, and transformation leads building internal buy-in for technology roadmaps CHROs and people leaders reshaping roles around AI-augmented work Industry conferences addressing senior commercial and technology audiences Audience outcomes A shared vocabulary across the executive team for AI, generative AI, and adjacent technologies A concrete short list of next actions, drawn from the Curious Five framework, tailored to the brief Sharper judgement on which vendor claims and use cases deserve investment and which do not A clearer view of where AI changes roles, processes, and customer experience inside their own organisation

Why organisations work with Anders Indset His Quantum Economy framework gives organisations a named argument for what comes after digitalization – not a call to “transform,” but a specific claim: that existing economic and organisational models require a philosophical upgrade, and that human potential, not technology alone, determines what follows. He coined the concept of the “Final Narcissistic Injury of Humankind” – the argument that AI’s deepest threat is not job displacement but the erosion of human agency and self-perception. This gives boards and executive teams a precise vocabulary for what is genuinely at stake in AI strategy. His “Anticipated Future” concept reframes strategic foresight as a leadership competency: the capacity to project forward from exponential data rather than extrapolate backwards from historical analysis. It is a directly applicable decision-making discipline, not a futurist premise. As an early investor in Terra Quantum AG and founder of the Njordis Group, his perspectives on deep tech are grounded in active investment decisions – meaning his claims about emerging technology have been stress-tested against real capital allocation. He has co-authored peer-reviewed philosophical and scientific papers with physicist Florian Neukart on the simulation hypothesis and the convergence of AI and human intelligence (AHI) – providing a rigour of argument that distinguishes him from commentators working purely at the level of narrative. Biography highlights Four Spiegel bestselling books – Wild Knowledge, The Quantum Economy, Das infizierte Denken, The Viking Code – translated into more than ten languages Named to Thinkers50 Radar 2018 among 30 Global Thinkers most likely to shape the future of organisational leadership; 2019 Breakthrough Idea Award finalist for The Quantum Economy Founder, Global Institute of Leadership and Technology (GILT), 2012; Founder and Chairman, Njordis Group (venture capital and advisory) Early investor and advisory board member, Terra Quantum AG; supervisory board member, German Tech Entrepreneurship Center (GTEC) Keynote speaker at the World Economic Forum, Global HR Summit, and Mobile World Congress; over 1,500 presentations across more than 60 countries Media coverage in Fast Company, Forbes, Fortune, Frankfurter Allgemeine Zeitung, NZZ, and Harvard Business Manager Dubbed “Rock’n’Roll Plato” by European media; guest lecturer at leading international business schools Biography Anders Indset’s central argument is simple and uncomfortable: in a world with near-unlimited access to information, knowledge is no longer the scarce resource for leaders – understanding is. His work begins where most AI and technology commentary stops, asking not what technology can do but what it means for human decision-making, economic design, and organisational purpose. His 2019 Spiegel bestseller The Quantum Economy introduced the concept of a post-digital economic framework – a named thesis, not a trend report – arguing that capitalism requires a philosophical upgrade to remain compatible with human values as algorithms become authorities. The book was a finalist for the Thinkers50 Breakthrough Idea Award and reached number one on the Manager Magazin business book chart. Subsequent books – including The Viking Code (2024) and The Singularity Paradox (2025, co-authored with physicist Florian Neukart) – have extended the framework into culture, values-driven leadership, and the emergence of what Indset and Neukart term Artificial Human Intelligence (AHI): the argument that a conscious, human-centred response to superintelligence is both possible and necessary. Indset is not a commentator at a distance from the technologies he describes. As an early investor in Terra Quantum AG and founder of the Njordis Group, he has made active capital commitments in quantum computing, AI, healthtech, and cybersecurity. This positions his philosophical arguments inside real decisions about where exponential technology is heading – not above them. He has spoken at the World Economic Forum, the Global HR Summit, and Mobile World Congress, and his work has appeared in Fast Company, Forbes, Fortune, and the Frankfurter Allgemeine Zeitung. For organisations navigating the question of what leadership actually means when AI can outperform human cognition on an expanding range of tasks, Indset offers something specific: a systematic philosophical framework, tested in print, in investment, and across executive audiences in more than 60 countries. Key speaking topics The Quantum Economy and post-digital capitalism Artificial intelligence and human agency Exponential technology and organisational strategy Anticipated Future as a leadership discipline Artificial Human Intelligence (AHI) and the technological singularity Values-driven performance culture Philosophical foundations of strategic decision-making Ideal for C-suite and board-level audiences wrestling with the strategic and existential implications of AI Technology, innovation, and strategy leadership conferences Executive development programmes exploring the relationship between philosophy, leadership, and emerging technology Policy and business forums on the future of economies and social structures in an AI-accelerated world Audience outcomes A named, book-backed conceptual vocabulary – Quantum Economy, Anticipated Future, Possibilism – for framing strategic thinking about technology beyond trend language A sharper distinction between information access and organisational wisdom, and why the gap between them is the real leadership challenge of the AI era Specific philosophical tools for exercising anticipatory leadership: projecting forward from exponential change rather than extrapolating from historical data A reframing of AI risk – moving beyond job displacement to the deeper question of human agency, purpose, and self-determination in technology-driven organisations A perspective on performance culture grounded in values and collective intelligence, drawing on the Viking Code framework

Why organisations work with Adam Cheyer He built the original Siri – not from a single insight but through more than a decade of AI research at SRI International – and then rebuilt the paradigm at Samsung and Airbnb. That depth of iteration, across platforms and at scale, is not replicated elsewhere on the speaking circuit. Four of his five ventures were acquired specifically for their AI technology, by Apple, Samsung, Airbnb, and Cognizant. The acquisitions validate not just the product but the engineering and commercial judgements behind it. After each acquisition, he stayed and led AI integration inside the acquiring organisation. Most founders don’t stay for that part – which is where AI strategies most commonly fail. He was ranked #2 on Voicebot.ai‘s Top Visionaries in Voice 2019 – behind Jeff Bezos and ahead of Sundar Pichai – while actively deploying conversational AI inside Samsung’s global platform. His foundation at SRI International as Chief Architect of CALO/PAL – the US government’s largest AI project, funded by DARPA – means his commercial instincts are grounded in the actual science of how intelligent systems work. Biography highlights Co-founder of Siri, Inc.; Director of Engineering, iPhone/iOS group, Apple – led AI and server-side development for Siri across more than 500 million devices Co-founder and VP R&D, Viv Labs, acquired by Samsung in 2016; Viv became the technical foundation for Samsung’s Bixby Chief Architect, CALO/PAL project, SRI International – the US government’s largest-funded AI research programme, funded by DARPA Co-founder and CEO, GamePlanner.AI, acquired by Airbnb (late 2023, est. ~$200M); VP AI Experience, Airbnb Founding member, Change.org; co-founder, Sentient Technologies (acquired by Cognizant) 60+ peer-reviewed publications; 50+ patents across AI, machine learning, distributed computing, and conversational systems Ranked #2, Voicebot.ai Top Visionaries in Voice 2019; 2024 Brandeis Alumni Achievement Award; TechCrunch Crunchies Award for Best Technology Achievement Scientific Advisory Board member, Allen Institute for Artificial Intelligence (AI2) Biography Building an AI product that works in a controlled environment and scaling it to hundreds of millions of users are different engineering problems. Most organisations now committing to AI strategies have very few people in the room who have done the second – and fewer still who have done it multiple times, across different platforms, inside multiple large organisations. Adam Cheyer spent more than a decade at SRI International as Chief Architect of CALO/PAL – the US government’s largest AI research programme, funded by DARPA – before co-founding Siri, Inc. in 2007 with Dag Kittlaus and Tom Gruber. When Apple acquired the company in 2010, he stayed as Director of Engineering in the iPhone/iOS group, leading the AI and server-side development that put Siri on more than 500 million devices. He has repeated this cycle three more times. Viv Labs, which he co-founded and led as VP R&D, was acquired by Samsung in 2016 and became the technical foundation for Bixby. Sentient Technologies – an early large-scale distributed machine learning platform – was acquired by Cognizant. GamePlanner.AI was acquired by Airbnb in late 2023, where Cheyer served as VP AI Experience, applying generative AI to transform how users engage with the platform. He holds more than 50 patents and has authored more than 60 peer-reviewed publications in AI, machine learning, and conversational systems. He serves on the Scientific Advisory Board of the Allen Institute for Artificial Intelligence and received the 2024 Brandeis Alumni Achievement Award for contributions to technology entrepreneurship. Key speaking topics Conversational AI and intelligent personal assistants Generative AI and enterprise application AI product development and commercial scaling Technology entrepreneurship and venture building Human-computer interaction and intelligent interfaces Large-scale and distributed machine learning AI integration in consumer and enterprise platforms Ideal for Chief Technology Officers and product leadership teams navigating AI product strategy Innovation and R&D functions evaluating AI investment decisions Executive and board audiences assessing AI-enabled product development or acquisition C-suite leaders who need a practitioner’s account of where AI integration succeeds and where it fails Audience outcomes A practitioner’s account of how conversational and generative AI systems are designed, built, and scaled – distinct from analyst or vendor perspectives Understanding of the architectural and organisational decisions that determine whether AI products deliver at scale Direct insight into how Apple, Samsung, and Airbnb have each integrated acquired AI technology into their core platforms Lessons from founding, scaling, and exiting AI ventures across four separate acquisition cycles A grounded, evidence-based framework for assessing which AI capabilities are commercially transformational and which remain overstated

Why organisations work with Vivienne Ming Her «Tax on Being Different» framework quantifies – in economic and productivity terms – the cost organisations pay when marginalised workers must expend extra effort just to be assessed as equivalent. This is a measurement argument with commercial implications, not a values one. As Chief Scientist at Gild, she built machine learning models trained on 122 million professionals, making her one of the few people who has directly operationalised predictive AI for talent assessment at scale, outside a purely academic context. She reframes diversity from a compliance question into an optimisation problem: one that can be modelled, measured, and corrected using the same tools organisations already apply to operational decisions. Her research spans workforce, education, and health, giving her an unusually broad evidence base for what actually predicts long-term human capability, and what doesn’t. Published in Nature and Neural Information Processing Systems, and holding academic appointments at UC Berkeley and UCL, her arguments carry institutional credibility that applied consultants and conference speakers typically cannot match. Biography highlights Author of Robot-Proof: When Machines Have All the Answers, Build Better People (Wiley, 2026), which argues that human capital – not AI capability – determines the outcome of human-machine collaboration PhD in Psychology from Carnegie Mellon University; joint postdoctoral fellowship at Stanford University and UC Berkeley’s Redwood Center for Theoretical Neuroscience Former Chief Scientist at Gild, where she built ML models trained on 122 million professionals to assess human capability beyond conventional credentials Founder and Executive Chair of Socos Labs, an independent research institute applying AI and neuroscience to workforce, education, and health challenges Research published in Nature, Neural Information Processing Systems, and Neural Computation Ranked #5 on the Financial Times / OUTstanding list of the world’s top LGBT executives (2017); named BBC 100 Women (2017) and Inc. Magazine’s «10 Women to Watch in Tech» Chair, UC Berkeley Neurotech Collider Hub; Honorary Professor, UCL Global Business School for Health; board member, RFK Human Rights Biography Vivienne Ming built her career on a discomforting empirical observation: the hiring signals organisations treat as reliable – degrees, interview performance, institutional pedigree – do not predict what they claim to predict. She tested this at scale. As Chief Scientist at Gild, she developed machine learning models trained on data from 122 million professionals, looking for what actually distinguishes high performers from credentialled ones. The gap was substantial. Most organisations were optimising for proxies, not capability. That finding runs through everything she has done since. At Socos Labs, the research institute she co-founded with her wife Dr. Norma Ming, she has extended the question into education and health, examining what psychological constructs genuinely predict long-term life outcomes, and publishing that research in Nature and Neural Information Processing Systems. The argument is consistent: measurement systems in organisations are systematically broken, and the cost is borne most heavily by those who don’t fit the template. Her book Robot-Proof: When Machines Have All the Answers, Build Better People (Wiley, 2026) extends that argument into AI, making the case that human capital – not model benchmarks – determines whether human-machine collaboration produces anything beyond substitution. Her «Tax on Being Different» framework gives that cost a number. Drawing on large-scale HR data, it quantifies the additional credential burden that women, people of colour, and LGBTQ+ individuals absorb to be evaluated on equivalent terms. This is not a cultural argument. It is a productivity and innovation argument: one that has been delivered to boards and leadership teams at Google, Deloitte, and Salesforce, and presented at the Royal Society. She holds a PhD in Psychology from Carnegie Mellon University, with joint postdoctoral appointments at Stanford and UC Berkeley. She chairs the UC Berkeley Neurotech Collider Hub, holds an honorary professorship at UCL’s Global Business School for Health, and serves on the board of RFK Human Rights. In 2017, she was ranked #5 on the Financial Times / OUTstanding list of the world’s top LGBT executives. Her research and commentary have been featured in the Financial Times, Business Insider, Fast Company, and CNBC. Key speaking topics AI and predictive modelling of human capability The economics of talent assessment and bias Neuroscience of decision-making in organisations Diversity, inclusion, and the productivity cost of difference Human-machine collective intelligence AI applications in education, health, and workforce development Innovation methodology: solving ill-posed problems Ideal for CHROs and talent acquisition leaders reviewing whether their hiring signals are predictive CEOs and boards integrating AI into people decisions and workforce strategy DEI leaders seeking evidence-based, commercially framed arguments for systemic change Technology and innovation functions examining the limits and applications of AI in human contexts Audience outcomes A quantified, data-grounded understanding of what broken talent systems cost organisations in productivity and innovation A concrete reframe of diversity: not a moral obligation but a measurement and optimisation problem Practical questions to apply to their own hiring, promotion, and development processes Clarity on where AI reliably improves human assessment – and where it perpetuates the biases already embedded in the data A new vocabulary for capability that moves beyond credentials and credentials-adjacent signals