Data Analytics

Why organisations work with Cassie Kozyrkov She built the Decision Intelligence function inside Google from scratch and ran it for five years, which means leaders get advice from someone who has already solved, at scale, the problem they are trying to solve. She named and codified the field itself. When a CEO asks what Decision Intelligence is and why their AI investment should sit inside it, she is the primary source, not an interpreter of someone else’s framework. She personally trained more than 20,000 Googlers across every function in data-driven decision-making and AI, so she knows how to make the material land with non-technical executives as well as engineers. She translates AI and statistics into decision-language that boards and operators can use. Her Making Friends with Machine Learning course, originally built only for Google, is now the reference explainer for thousands of leaders outside the company. She advises at the level the material requires. Her Federal Reserve Bank of New York Innovation Advisory Council seat and her work with Forbes on AI signal that her analysis is taken seriously by policy and media institutions, not only by corporate buyers. Biography highlights Google’s first Chief Decision Scientist (2018 to 2023), leading the firm’s decision intelligence practice inside Research and Machine Intelligence. Founder and CEO of Kozyr, an AI advisory and education business serving senior leaders and their teams. Personally trained more than 20,000 Googlers in data-driven decision-making and AI, and guided over 500 decision intelligence projects inside Google. Creator of Making Friends with Machine Learning, originally an internal Google course, now a free public course on YouTube. Author of the Decision Intelligence Substack and LinkedIn Top Voice for six consecutive years; writing has appeared in Harvard Business Review, Fortune, Fast Company, WIRED, and The Wall Street Journal. Member of the Federal Reserve Bank of New York’s Innovation Advisory Council (2023 to 2024); Duke University Few-Glasson Distinguished Alumna. Biography Most companies do not have a data problem, they have a decision problem. The dashboards, pipelines, and models are in place, and yet senior leaders still cannot say which decisions are demonstrably better because of any of it. That gap is the subject Cassie Kozyrkov has been working on for a decade, first inside Google and now with leaders across industries. At Google, she became the company’s first Chief Decision Scientist in 2018 and held the role until 2023. She built a new function that sat between Research and Machine Intelligence on one side and the operating business on the other, and used it to run AI and data through a discipline she calls Decision Intelligence. By the time she left, she had personally trained more than 20,000 Googlers and influenced over 500 projects against that framework. The reason her work travels beyond Google is that she made the material legible. Her course Making Friends with Machine Learning, built inside Google and later released in full on YouTube, is one of the few genuinely plain-English explainers of how machine learning actually fits into business decisions. Her writing in Harvard Business Review, Fortune, Fast Company, WIRED, and The Wall Street Journal has done the same for non-technical executives, and her Decision Intelligence Substack has become a working reference for practitioners. Today she runs Kozyr, advising leadership teams on AI strategy and decision design, and sits on the Federal Reserve Bank of New York’s Innovation Advisory Council on AI and financial markets. The through-line is consistent. She is the rare AI voice who starts with the decision the organisation is trying to get right, and works backwards to the technology, rather than the other way round. Key speaking topics Decision Intelligence AI strategy and adoption Data-driven decision-making Machine learning for business leaders Responsible and effective use of AI AI literacy for executives Bias and judgement in AI systems Ideal for CEOs, boards, and executive teams setting AI strategy and capital allocation against it Chief Data, Analytics, and AI Officers building a decision-intelligence operating model Transformation and strategy leaders responsible for turning AI pilots into business results Leadership programmes and offsites that need genuine AI literacy, not a vendor pitch Audience outcomes A working definition of Decision Intelligence and where it sits relative to data science, analytics, and AI investment. A sharper diagnostic for why AI projects stall: wrong decision scoped, wrong owner, or wrong question asked of the model. Shared language across technical and non-technical leaders for debating AI initiatives without defaulting to buzzwords. Specific techniques for pressure-testing decisions against common biases, including outcome bias and confirmation bias. A realistic read on what current AI systems can and cannot be trusted to decide without human judgement in the loop.

Why organisations work with Miloš Maričić He gives investment boards a working diagnostic for distinguishing real machine learning from AI marketing, anchored in his SPEC framework and his CFA Institute Enterprising Investor work on weak quant models. He chairs Executive AI, the network of CEOs of major European institutional investment organisations, and represented that industry in the EU Artificial Intelligence Act standardisation process. Few speakers can describe AI regulation from inside the room where the rules were written. He has co-edited the Routledge Handbook of Artificial Intelligence and Philanthropy with the University of Geneva, the standard reference for AI in the social sector. That gives foundations and philanthropic boards a credible voice on the same subject. He has built and exited two AI companies and ranks in the top five per cent of the Numerai global leaderboard for market prediction models, so the technical claim is matched by personal track record. He is an OECD AI Expert and a World Economic Forum contributor, which means his framing is already calibrated for senior policy and regulatory audiences. Biography highlights Founder of the Altruist League, Geneva, a philanthropy consultancy whose network reports AUM above USD 10 billion. Chair of Executive AI, a network of CEOs of major European institutional investment organisations. AI Expert at the OECD and contributor at the World Economic Forum. Co-editor, The Routledge Handbook of Artificial Intelligence and Philanthropy, Routledge, 2024. Co-author, Fixing Philanthropy: Six Principles for Actually Improving the World When Giving Away Money, 2021. Educated at the London School of Economics, New York University and Harvard Business School. Biography Most institutional investors now have AI somewhere in their portfolio, their managers, or their operations. Very few have a working method for telling genuine machine learning from a factor model dressed up for a board meeting. That is the gap Maričić has spent his career filling, first inside his own AI ventures, now as Chair of Executive AI, the network of CEOs of major European institutional investment organisations. His SPEC framework, developed for capital allocators and published through CFA Institute’s Enterprising Investor, gives investment committees a short diagnostic for evaluating quantitative managers who claim AI capability. It is the kind of practical tool a CIO can take into a manager meeting on Monday morning. He represented the institutional investor industry in the EU Artificial Intelligence Act standardisation process, and serves as an AI Expert at the OECD and a contributor at the World Economic Forum. Maričić founded the Altruist League, a Geneva-based philanthropy consultancy that pioneered the use of AI in sourcing investments, distributing funds and managing portfolios, and whose network now reports AUM above USD 10 billion. With Giuseppe Ugazio at the University of Geneva, he co-edited The Routledge Handbook of Artificial Intelligence and Philanthropy, the 2024 reference work for foundations and social sector boards thinking about AI governance. He is educated at the London School of Economics, NYU and Harvard Business School, ranks in the top five per cent of the Numerai global leaderboard for market prediction models, and writes The Specification, a newsletter that translates frontier AI research into practical tools for institutional allocators. Key speaking topics AI governance for investment boards and fiduciary committees Due diligence on machine learning in quantitative investment strategies AI regulation, the EU AI Act and institutional capital allocation AI in philanthropy and the social sector Causal inference and the limits of factor investing Geopolitics of AI for sovereign wealth funds and central banks Trust-based giving and systemic-change philanthropy Ideal for Chief Investment Officers, investment committees and manager-selection teams at pension funds, sovereign wealth funds, central banks and endowments Boards of foundations and philanthropic organisations setting AI strategy and governance Risk, audit and fiduciary committees taking responsibility for AI-driven strategies they did not build Senior policy and regulatory audiences working on AI in financial services Audience outcomes A clear diagnostic for distinguishing real machine learning from AI marketing inside quantitative managers Specific questions a board or investment committee can put to managers and internal teams about AI claims A current read on the EU AI Act and what it means for institutional allocators in practice A grounded view of where AI is genuinely changing philanthropy and where it is hype A working vocabulary for fiduciary AI oversight that does not require a technical background

Why organisations work with David McCandless He built the language of modern editorial data visualisation through Information is Beautiful, the blog and three books that defined the form for a generation of journalists and designers. He co-founded the Information is Beautiful Awards in 2012 with Kantar’s Aziz Cami, the global benchmark prize for data visualisation, giving him a panoramic view of what works across thousands of submissions. His work has been published by The Guardian, Wired, and Die Zeit and exhibited at MoMA, Tate Britain, and the Wellcome Trust gallery, evidence that the craft holds up to both editorial and curatorial scrutiny. His TEDGlobal 2010 talk, “The beauty of data visualization”, remains one of the most-watched introductions to the field and shapes how senior audiences think about visual storytelling. Biography highlights Author of Information is Beautiful (2009), Knowledge is Beautiful (2014), and Beautiful News (2023), published by HarperCollins. Founder of the Information is Beautiful blog and co-founder of the Kantar Information is Beautiful Awards (2012). TEDGlobal 2010 speaker: “The beauty of data visualization”. Information design featured in The Guardian, Wired, and Die Zeit. Work exhibited at the Museum of Modern Art (New York), Tate Britain, and the Wellcome Trust gallery (London). Began his career as a journalist writing for The Guardian and Wired before building Information is Beautiful into a publishing platform. Biography The hardest problem in modern communication is not gathering data. It is making the data mean something to a reader who has eight seconds and a phone. That is the territory David McCandless has worked for nearly two decades, first as a journalist at The Guardian and Wired, then as the founder of Information is Beautiful. The blog became a publishing programme. Information is Beautiful (2009), Knowledge is Beautiful (2014), and Beautiful News (2023) collect more than 1,500 graphics that take subjects ranging from drug deaths to global wealth and turn them into images a non-specialist can read. The craft sits in the choices: what to compare, what to leave out, what visual metaphor lets a number argue with itself. In 2012 he co-founded what became the Kantar Information is Beautiful Awards with Aziz Cami, then Creative Director at Kantar. Through that platform McCandless has spent more than a decade looking at the best data visualisation work in the world, which gives him an unusually wide reference set when advising teams on what separates a chart that lands from one that does not. His work has been exhibited at the Museum of Modern Art, Tate Britain, and the Wellcome Trust gallery, and his TEDGlobal 2010 talk on the beauty of data visualisation introduced the field to a mainstream audience. For organisations sitting on data they cannot translate into action, he offers the rarer skill: editorial judgement on what is worth showing, and how. Key speaking topics Data visualisation Information design Data storytelling Data journalism Visual communication Creativity and pattern recognition Infographics in business communication Ideal for CMOs, brand and marketing leaders rethinking how data shapes customer narratives Communications, internal comms, and corporate affairs leads briefing senior audiences Heads of data, analytics, and insight whose dashboards are not changing decisions Innovation and design leaders building visual literacy across the organisation Audience outcomes A working vocabulary for what makes a data visualisation land with a non-specialist audience Sharper editorial judgement on which numbers in a dataset are worth showing and which are noise Concrete examples from across journalism, design, and the IIB Awards archive of what good looks like A clearer view of how to brief designers, agencies, and internal teams on data-led communication

Why organisations work with Adrian Joseph He has run an AI and data function of roughly 1,600 people inside a FTSE 100 company, so his advice to boards reflects what it takes to deliver at that scale, not what a strategy deck suggests. He sits on the boards of Direct Line, Allwyn and Great Ormond Street Hospital, giving him a current view of how AI lands in insurance, gaming and healthcare rather than a single-sector perspective. As an Expert Member of the UK AI Council he contributed to the National AI Strategy, so he reads regulation and policy as someone who has been inside the room, not as an outside observer. He holds an OBE for services to equality and diversity in business and was named the UK’s most influential minority ethnic technology leader by the Financial Times and Inclusive Boards, which sharpens his credibility on the workforce side of AI transformation. His career path through Google, EY and BT gives audiences a rare triangulation: the hyperscaler view of what the technology can do, the consulting view of how to sell change internally, and the operator view of what actually breaks. Biography highlights Former Chief Data and AI Officer, BT Group, leading approximately 1,600 data and AI professionals. Former Senior Partner and Head of UK Data and Analytics for Financial Services at EY. Over ten years in senior leadership roles at Google across cloud, digital and data science. Non-Executive Director at Direct Line Insurance Group, Allwyn UK and Great Ormond Street Hospital NHS Foundation Trust. Expert Member of the UK Government’s AI Council and former Non-Executive Director at the Home Office. OBE for services to equality and diversity in business; named the UK’s most influential BAME technology leader by the Financial Times and Inclusive Boards. Biography Running an AI and data function of 1,600 people inside BT Group taught Adrian Joseph OBE what most board conversations about AI miss. The commercial case is not won in the model. It is won in the operating model, the talent pipeline and the patience of the leadership team to let value compound. That operator’s view is what he brings into the room. Before BT, he spent over a decade at Google in senior cloud, digital and data science roles, then led the UK Data and Analytics practice for Financial Services at EY as a Senior Partner. The path gives him three lenses on the same problem. Hyperscalers built the infrastructure. Consultancies sold the transformation story. Incumbents have to actually run the thing in production under regulatory scrutiny. He currently holds non-executive director roles at Direct Line Insurance Group, Allwyn UK, the National Lottery operator, and Great Ormond Street Hospital for Children NHS Foundation Trust, and sits on the Technology Advisory Board at NatWest Group. As an Expert Member of the UK Government’s AI Council he contributed to the National AI Strategy, and served as a Non-Executive Director at the Home Office from 2015 to 2020. He was awarded an OBE in the 2019 New Year’s Honours for services to equality and diversity in business, and the Financial Times and Inclusive Boards named him the UK’s most influential Black, Asian and ethnic minority technology leader. That recognition is not decoration on the CV. It sharpens his argument that the AI advantage large organisations seek is inseparable from who they let build and govern the systems. Key speaking topics Enterprise AI strategy and commercial return Responsible AI and governance Data and AI operating models at scale Digital and cloud transformation in regulated industries AI policy and the National AI Strategy Diversity and inclusion in technology leadership Board-level oversight of AI risk Ideal for CEOs, CFOs and boards under pressure to show commercial return from AI and data spend Chief Data Officers, CIOs and CTOs building or restructuring AI and data functions Financial services, insurance, healthcare and public sector leaders navigating AI in regulated environments CHROs and transformation leads addressing the talent and inclusion dimension of AI adoption Audience outcomes A sharper line between AI activity that produces commercial return and AI activity that produces slides A realistic view of what an AI and data operating model looks like at enterprise scale, from someone who ran one Current reading of UK AI policy and regulation from inside the AI Council and National AI Strategy work Practical signals for boards on where to probe AI risk, governance and delivery maturity Language for connecting AI capability to workforce, talent and inclusion strategy

Why organisations work with Paddy Lowe He has industrialised winning at three Formula 1 constructors and can show, from inside the engineering room, how a championship operation actually allocates capital, talent and risk. He runs Zero Petroleum, the company behind the Guinness-verified first flight on 100 percent synthetic fuel, which gives him a working answer to the question of how aviation and motorsport decarbonise without waiting for batteries. His authority on energy transition is operational, not advocacy: a Fellow of the Royal Academy of Engineering speaking from a fuel plant, not a policy podium. He bridges the two conversations that boards now run in parallel, hard-edged engineering performance under pressure and the capital reality of net zero, which most speakers handle separately. Biography highlights 32 years in Formula 1 across Williams, McLaren and Mercedes; technical leadership behind cars that won 12 World Championships and 158 Grands Prix. Technical Director at McLaren, then Executive Director (Technical) at Mercedes during the team’s 2014 to 2016 dominance with Lewis Hamilton and Nico Rosberg. Co-founder and CEO of Zero Petroleum, a UK synthetic fuel company producing fossil-free drop-in fuels from atmospheric CO2 and renewable hydrogen. Holder of the Guinness World Record with the Royal Air Force for the first aircraft flight powered entirely by synthetic fuel, achieved at Cotswold Airport in November 2021. Fellow of the Royal Academy of Engineering, elected 2015. Engineering graduate of Sidney Sussex College, Cambridge, and Honorary Fellow of the College. Biography Mercedes won 51 of 59 Grands Prix between 2014 and 2016. Paddy Lowe was the Executive Director responsible for the technical organisation that made that possible, after a decade as Technical Director at McLaren and an earlier career at Williams developing the active suspension that delivered the 1992 titles. Three constructors, twelve World Championships, one common pattern: an engineering culture built to convert money and time into measurable performance under public scrutiny. That track record is the credential. The substantive work he now talks to boards about is different. In 2020 he co-founded Zero Petroleum, a synthetic fuel company that combines atmospheric carbon dioxide with renewable hydrogen to produce fossil-free, drop-in liquid fuels. The point is not laboratory novelty. The point is that aviation, motorsport, shipping and the global classic vehicle base will run on hydrocarbons for decades, and decarbonising them needs molecules, not only electrons. The proof exists. In November 2021, Zero Petroleum and the Royal Air Force flew an aircraft on 100 percent synthetic fuel and were awarded a Guinness World Record for the first such flight. Formula 1 has since committed to fully sustainable fuels, and Lowe has been a public technical voice in the policy conversation around how that transition is engineered and financed. For a senior buyer, the value is operational specificity. He explains how engineering organisations win against deadlines, how data and simulation reshape decision-making at the top of an organisation, and what it actually takes, in capital, regulation and supply, to move a heavy industry off fossil fuel. Key speaking topics Synthetic fuels and the energy transition in aviation, motorsport and heavy transport Net zero strategy beyond electrification Engineering performance under competitive pressure Data-led decision making in high-stakes operations Innovation and R&D leadership in regulated industries Lessons from Formula 1 championship organisations Ideal for Boards and executive teams in aviation, automotive, energy and industrial groups facing a credible decarbonisation deadline CTOs, Chief Sustainability Officers and Heads of R&D scoping practical low-carbon liquid fuel pathways Strategy and transformation leads benchmarking high-performance engineering cultures Investor days, supplier summits and policy forums where the audience needs a working voice on the energy transition Audience outcomes A clearer view of how aviation, motorsport and other liquid-fuel sectors can decarbonise without waiting for full electrification A working sense of how a Formula 1 technical organisation converts data, simulation and capital into repeatable performance A sharper read on which net zero claims are engineered and financed, and which are still rhetorical Specific examples of what it takes, in regulation, supply chain and certification, to move a synthetic fuel from prototype to commercial flight

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 Peter Field His IPA Effectiveness Databank analysis – spanning over 1,000 campaigns, 80+ categories, and 30 years – gives senior marketers an empirical base for budget decisions that no internal dataset can match in scale or authority. The 60:40 principle he co-established with Les Binet is now the dominant reference point for CMO-level investment decisions globally; organisations use it to resist short-term pressure from finance and hold the case for brand building with the board. His 2019 Crisis in Creative Effectiveness report – showing that creatively-awarded campaigns had lost their effectiveness advantage entirely due to short-termism – gives marketing leaders the evidence to argue for sustained creative investment rather than disposable activation. The Creative Effectiveness Ladder, co-developed with James Hurman for Cannes Lions and WARC, gives organisations a practical evaluation tool for assessing the long-term ambition of creative work before it runs. His extension of effectiveness principles into B2B – The Five Principles of Growth in B2B Marketing – fills an empirical gap that most B2B marketing leaders have had to navigate without equivalent guidance. Biography highlights Cambridge graduate; 15 years as a strategic planner at advertising agencies including BMP (later part of the DDB network) Co-author with Les Binet of the IPA Effectiveness Databank series: Marketing in the Era of Accountability (2007), The Long & The Short of It (2013), Media in Focus (2017), Effectiveness in Context (2018) Author of The Crisis in Creative Effectiveness (IPA, 2019) – analysing 24 years of data on the declining relationship between creative awards and business outcomes Co-author with James Hurman of The Effectiveness Code (Cannes Lions/WARC, 2020), which produced the Creative Effectiveness Ladder framework Honorary Fellow of the UK Institute of Practitioners in Advertising Regular keynote speaker at the Cannes Lions Festival of Creativity, IPA EffWeek, and WARC Sessions Biography Marketing measurement has a structural flaw: the channels easiest to measure in real time are the ones least suited to building durable growth. Peter Field has spent 25 years making that argument with evidence – the IPA Effectiveness Databank, a repository of independently verified advertising effectiveness data spanning more than three decades. With Les Binet, Field co-authored the series of IPA Effectiveness Databank reports that set the empirical terms for decisions about budget allocation, media strategy, and creative investment. The Long and the Short of It (2013) established the 60:40 principle: most organisations systematically under-invest in brand building relative to short-term activation. Long-term emotional campaigns, the data showed, generate roughly double the profit of short-term approaches. The series has been cited in over 70 international academic publications and textbooks. Field’s solo research extended these findings into the relationship between creativity and effectiveness. The Crisis in Creative Effectiveness (IPA, 2019) revealed that creatively-awarded campaigns had become no more effective than non-awarded ones – the first time in 24 years of data – driven by the industry’s shift toward short-term activation work. His co-authored Creative Effectiveness Ladder, developed with James Hurman for Cannes Lions and WARC, provides a practical framework for evaluating the long-term ambition of creative work before it runs. A Cambridge graduate and former strategic planner at BMP, Field is an Honorary Fellow of the UK Institute of Practitioners in Advertising. His research has been presented at Cannes Lions, WARC Sessions, and IPA EffWeek, and has shaped how CMOs, CFOs, and boards across the world evaluate the returns on marketing investment. Key speaking topics Marketing effectiveness and budget allocation Long-term brand building vs. short-term sales activation Creative effectiveness and the business case for creativity Measurement, metrics, and the limits of digital attribution Brand growth and pricing power B2B marketing effectiveness Evidence-based commercial strategy Ideal for CMOs and senior marketing leaders under short-term commercial pressure from CFOs or boards CFOs and CEOs seeking an empirical framework for evaluating marketing investment decisions Brand and creative strategy leads making the case for long-term creative ambition internally B2B marketing directors who have lacked an effectiveness evidence base equivalent to B2C Audience outcomes A clear, evidence-based framework for allocating budget between brand building and short-term activation – grounded in 30+ years of campaign data A working understanding of why short-term digital metrics can systematically mislead commercial decision-making The analytical language to present the commercial case for brand investment to a CFO or board Practical criteria for evaluating whether a creative strategy is built for long-term effectiveness or short-term efficiency Awareness of how the Five Principles of Growth in B2B Marketing translate consumer effectiveness evidence into B2B strategy

Why organisations work with Carme Artigas Access to the EU AI Act from the inside: as the Council Presidency’s chief negotiator when the Act was concluded in December 2023, she knows which provisions were contested, how they were resolved, and where enforcement questions remain open – clarity that no commentator or academic can replicate. A UN-level governance map built from the source: as Co-Chair of the UN High-Level Advisory Body on AI, she coordinated 39 experts across 33 countries to produce Governing AI for Humanity – the blueprint for global AI oversight that national strategies and multilateral institutions are now implementing. She co-chaired the body alongside Google Senior Vice President James Manyika. A regulatory perspective grounded in commercial reality: she co-founded Synergic Partners and built it to 150 data scientists before Telefónica acquired it in 2015. Her understanding of AI governance is not abstract – it is shaped by how data and AI deployments actually function inside commercial organisations. The only person to have designed a national AI governance system from the ground up: as Spain’s inaugural Secretary of State for Digitalisation and AI, she built the National AI Strategy, data economy strategy, digital rights charter, and the first AI supervision agency on the European continent – giving her unusually concrete insight into what governance implementation demands of organisations. An active research presence at the frontier: as a Senior Fellow at Harvard Kennedy School’s Belfer Center, she continues to work on current AI governance and technology policy questions alongside leading security and policy scholars – not recounting past decisions. Biography highlights Spain’s first Secretary of State for Digitalisation and Artificial Intelligence (2020–2023); simultaneously president of the National Cybersecurity Institute and the Spanish Agency for the Supervision of AI Chief Council negotiator for the EU AI Act, concluded under Spain’s Presidency of the Council of the European Union in December 2023 – the world’s first comprehensive legal framework for artificial intelligence Co-Chair, UN Secretary-General’s High-Level Advisory Body on Artificial Intelligence (2023–2024); co-produced Governing AI for Humanity with James Manyika (Google Senior Vice President) and 37 other experts from 33 countries Senior Fellow, Belfer Center for Science and International Affairs, Harvard Kennedy School; first Spanish woman to hold the position Co-founder and CEO, Synergic Partners – built to 150 data scientists, acquired by Telefónica in 2015; previously CEO of Ericsson Innova (Ericsson Group’s European venture capital fund) Women in Tech Global Awards 2025, Lifetime Achievement; Stanford University Ambassador for Women in Data Science; member of the European Council on Foreign Relations (ECFR) Biography The EU AI Act is the world’s first comprehensive legal framework for artificial intelligence. Its provisions determine which AI applications organisations can legally deploy, which require conformity assessments, and which are prohibited. Most executives know the regulation exists. Few understand its architecture. Carme Artigas did not comment on these negotiations – she led them. As Spain’s first Secretary of State for Digitalisation and AI, she was the Council Presidency’s chief negotiator when the EU AI Act was concluded in December 2023. She had already built the foundations from scratch: Spain’s National AI Strategy, digital rights charter, data economy strategy, and the first AI supervision agency on the European continent. In parallel, she co-chaired the United Nations High-Level Advisory Body on AI – a 39-member group spanning 33 countries, convened by Secretary-General Guterres in October 2023. The body’s final report, Governing AI for Humanity, published in September 2024, proposed the first architecture for inclusive global AI oversight. She co-chaired it alongside Google Senior Vice President James Manyika. Before government, she co-founded Synergic Partners – a big data consultancy she built to 150 data scientists before Telefónica acquired it in 2015, remaining as CEO through full integration into the Group. As a Senior Fellow at Harvard Kennedy School’s Belfer Center since 2023, she continues to engage with governance questions at the intersection of technology, security, and public policy. Key speaking topics EU AI Act implementation and strategic compliance Global AI governance frameworks AI governance and responsible AI deployment Data strategy and big data Digital transformation and national digital policy International technology cooperation and geopolitics of AI Women in technology and digital leadership Ideal for Boards and C-suites with active AI strategies navigating EU AI Act obligations and global regulatory exposure Chief Legal, Risk, and Compliance Officers mapping their organisation’s AI regulatory position Chief Digital and Technology Officers operating in or supplying to European markets Government and public sector leaders developing or stress-testing national AI governance frameworks Audience outcomes A clear understanding of what the EU AI Act actually requires – which AI applications are prohibited, which are designated high-risk, and what conformity assessment obligations apply Insight into how the global governance architecture is developing at UN level and how it intersects with European regulation A framework for elevating AI governance from a compliance function to a board-level strategic priority Understanding of where the regulatory fault lines remain open and where future enforcement is likely to concentrate Practical language and reference points to brief boards, regulators, and partners on AI governance obligations

Why organisations work with Anna Rosling Rönnlund Her Factfulness framework – co-developed with Hans and Ola Rosling and verified through Gapminder’s systematic global testing – gives leadership teams a named, testable inventory of the cognitive instincts that distort how they read global trends; knowing which instinct is operating is more actionable than being told to think more carefully about data. Dollar Street, the income-sorted photographic database she founded at Gapminder, organises 30,000+ images from 50+ countries by purchasing power rather than by geography – showing what global consumers actually look like at different spending levels in a way that statistical reports rarely achieve. She brings a combination almost nobody in this space can match: rigorous sociological training (Lund University), professional photography, senior UX design at Google, and twenty years building Gapminder’s data tools for mass, non-specialist audiences. Factfulness has sold over 2.5 million copies in 45+ languages; organisations engaging her work are connecting to a framework already embedded in business schools, executive education programmes, and corporate strategy teams internationally. She leads ESG and SDG literacy workshops using Gapminder’s verified, publicly available global datasets – giving organisations a grounded, non-ideological entry point to sustainability strategy built on measurable global reality rather than advocacy frameworks. Biography highlights Co-founder and VP, Head of Design and User Experience, Gapminder Foundation (est. 2005, Stockholm) Designed Trendalyzer – the animated bubble-chart visualisation tool – acquired by Google in 2007; Senior UX Designer, Google Mountain View (2007-2010) Co-author, Factfulness (Flatiron Books, 2018) – New York Times bestseller; 2.5 million+ copies sold; 45+ language editions Founder of Dollar Street (2016) – 30,000+ income-sorted photographs from 50+ countries, free under Creative Commons licence TED speaker (2017): “See how the rest of the world lives, organized by income” Honorary Doctorate in Informatics, University of Skövde (2018) Fast Company World Changing Ideas Award, Photography and Visualization category (2017) Biography Global strategy conversations are routinely shaped by assumptions that are decades out of date. Gapminder, the foundation Anna Rosling Rönnlund co-founded in 2005, was built to measure this problem precisely. It tests what people believe about the world, identifies where those beliefs are provably wrong, and develops tools to correct them. Her first major contribution was Trendalyzer, an animated visualisation tool she designed with Ola Rosling that made decades of development data readable in seconds. Google acquired it in 2007. When she and Ola returned to Gapminder in 2010, the mission shifted from visualisation to diagnosis: systematically testing what educated, experienced people get wrong about global development – and why. That diagnostic work produced Factfulness, co-authored with Hans Rosling and Ola Rosling and published in 2018. The book names ten cognitive instincts – including the gap instinct and the generalisation instinct – that cause leaders to systematically misread global trends. It became a New York Times bestseller, with over 2.5 million copies sold across 45 languages. Her parallel project, Dollar Street, sent photographers to 50+ countries to document everyday life at every income level – 30,000+ images, organised by purchasing power rather than geography. These images replace national stereotypes with income-level reality, giving organisations a concrete tool for understanding global consumers. Anna holds a Master’s in Sociology from Lund University and a Bachelor’s in Photography from Gothenburg University. She was awarded an Honorary Doctorate in Informatics from the University of Skövde in 2018 and received the Fast Company World Changing Ideas Award in the Photography and Visualization category in 2017. Key speaking topics Fact-based decision-making and the Factfulness framework Global development trends and emerging market realities Data visualisation and communicating complexity to non-specialist audiences Consumer demographics and income-level market analysis Dollar Street and visual approaches to global data ESG and SDG literacy for business Strategic misconceptions and cognitive bias in leadership Ideal for Boards and senior leadership teams making strategic decisions about global markets, risk, or emerging economies Chief Strategy Officers and heads of corporate strategy evaluating long-term assumptions and scenario plans Sustainability and ESG leads working with SDG frameworks and global impact data Leadership development and executive education programmes building data literacy and fact-based reasoning habits Audience outcomes A working understanding of the ten Factfulness instincts and how they distort strategic decision-making Practical methods for identifying and correcting the shared assumptions driving organisational strategy A reframed view of global consumer markets using Dollar Street’s income-level visual data, reducing reliance on outdated country stereotypes Greater confidence in questioning shared assumptions during leadership team discussions and board conversations Awareness of which global trends are measurably improving versus declining, grounded in Gapminder’s verified datasets

Why organisations work with Gary Foote He is a current F1 Chief Information Officer, now at GM Performance Power Units, building the technology function for the Cadillac F1 power unit programme from the ground up. He ran the IT and digital operation at Haas F1 for a decade, taking the team from a start-up entry in 2016 to a competitive, data-driven constructor with global infrastructure. His remit at Haas covered IT, digital, facilities, operations, ESG and business continuity, which gives boards a realistic view of how sustainability and technology intersect inside a performance business. He has been named in the UK CIO 100 for five consecutive years and is a Fellow of the British Computer Society, so the credibility holds up in a room of sitting CIOs. His track record spans Cosworth, Honda Racing F1, Brawn GP and Mercedes Grand Prix, covering six motorsport world championships, which lets him speak to high-performance culture without leaning on abstract frameworks. Biography highlights Chief Information Officer, GM Performance Power Units, the General Motors and TWG Global company delivering the Cadillac F1 power unit. Former CIO and Director of Sustainability at MoneyGram Haas F1 Team, a role held for approximately ten years. Earlier senior technology roles at Mercedes Grand Prix, Brawn GP, Honda Racing F1 and Cosworth Technology. Fellow of the British Computer Society. Named in the UK CIO 100 five years running, 2021 to 2025. Trustee at Tove Learning Trust and active advocate for STEM education. Biography Haas F1 arrived on the grid in 2016 with two cars, a lean headcount and a blank technology estate. Gary Foote built the IT and digital backbone that made that entry possible, then spent a decade scaling it into the stack of a competitive constructor. His brief at Haas eventually covered IT, digital, facilities, ESG and business continuity, which is a wider surface than most corporate CIO roles carry. That is the frame he brings to boards: technology strategy shaped by the realities of logistics, carbon reporting, risk and culture inside one business. Today he is CIO at GM Performance Power Units, the General Motors and TWG Global company set up to build the Cadillac F1 power unit. He is doing again what most CIOs never get the chance to do once, which is stand up an elite-sport technology function from a clean sheet while the competitive clock is already running. The credentials back the story. He is a Fellow of the British Computer Society and has been listed in the UK CIO 100 five years in a row. He writes and speaks in named industry outlets including Computer Weekly, Infosecurity Magazine and Celonis, and he sits on the board of Tove Learning Trust. Key speaking topics Technology leadership in high-performance sport Artificial intelligence and data strategy in Formula 1 Cybersecurity in time-critical operations Digital transformation inside elite teams Sustainability and ESG in motorsport Scaling an IT function from start-up to championship contender High-performance culture and cross-functional operations Ideal for CIO, CTO and CDO audiences looking at AI, data and infrastructure investment decisions Boards and executive teams benchmarking their operating model against high-tempo performance businesses Sustainability and ESG leaders in industrial and logistics-heavy sectors Audience outcomes A working picture of how a Formula 1 team uses data, AI and cloud infrastructure to compete race by race. A sharper view of how technology, facilities and ESG sit inside one leadership remit rather than separate silos. Practical reference points for scaling an IT function quickly without accruing legacy risk. A candid read on cybersecurity and business continuity in an environment where downtime is visible to the world.

Why organisations work with Sabrina Faramarzi She has written trend reports for The Future Laboratory, Stylus and Canvas8, three of the most-used forecasting houses in consumer strategy, so brand teams get a forecaster who knows how the foresight industry actually works inside. Her sector range covers travel, beauty, fashion, food and drink, wellbeing, money, tech, retail and media, which means a single speaker can address an audience drawn from several consumer-facing categories without losing specificity. She runs Are We Europe, a cross-border editorial operation, so she brings a pan-European read on culture and audience behaviour rather than a default Anglo-American lens. Her data storytelling practice through Dust in Translation is built for organisations that have research and data assets but cannot make them land with a non-technical audience. Biography highlights Managing Director, Are We Europe, a non-profit pan-European media collective. Founder and Editorial Director, Dust in Translation, a creative data storytelling agency. Co-founder, Feminist Internet, a non-profit advancing internet equality through creative practice. Trend reports written for The Future Laboratory, Stylus and Canvas8. Journalism contributions to The Guardian, Wired, Vice and Vogue Business. BA (Hons) First Class in Trend Prediction and Forecasting, University of East London; MA with Distinction in Journalism, University of the Arts London. Biography Most consumer trend conversations in the boardroom collapse into one of two failure modes. They either treat every TikTok spike as a strategic shift, or they ignore weak signals until a competitor has already built around them. Sabrina Faramarzi works in the gap between those two errors. Her practice is reading consumer and cultural signals well enough to tell a brand team which ones to bet on. She has the technical training for it. A First Class degree in Trend Prediction and Forecasting from the University of East London, an MA with Distinction in Journalism from the University of the Arts London, and a working track record writing trend reports for The Future Laboratory, Stylus and Canvas8. That is the inside of the foresight industry, not a commentator’s view of it. The journalism work runs alongside the forecasting. Bylines in The Guardian, Wired, Vice and Vogue Business cover gender, AI, digital rights and internet culture, and that editorial muscle is what lets her translate research into stories that boards and marketing teams actually use. Through Dust in Translation, her data storytelling agency, she does the same job for organisations sitting on data they cannot make legible. She also runs Are We Europe, a non-profit pan-European media collective, and co-founded Feminist Internet. Both give her something most trend speakers do not have: a structural view of how cultural narratives form and travel across borders, which is the part of trend work that matters most when a category is being reshaped rather than refreshed. Key speaking topics Consumer trend forecasting Data storytelling Internet culture and online communities Futures of consumer-facing industries Gender, AI and digital ethics Cross-border European media and audiences Ideal for CMOs, brand directors and category leads in consumer-facing businesses planning the next 18 to 36 months. Innovation and insights teams looking for an outside read on which signals to commit to. Communications and content leaders who need research and data turned into audience-ready stories. Conferences in travel, hospitality, beauty, fashion, food and drink, retail and media that want a sector-specific futures keynote. Audience outcomes A clearer sense of which consumer signals in their category are durable and which are noise. Working language for telling stories with data so research lands with non-technical audiences. A sharper read on how online communities form, mobilise and shape brand reputation. Sector-specific cues for where to look for the next category shift in travel, beauty, fashion, food, retail or media.

Why organisations work with Robert Smith He is a working AI researcher with more than 100 peer-reviewed papers, not a consultant translating other people’s science. When a board asks how a model actually behaves, he can answer at the level of the maths. His book Rage Inside the Machine sets out a specific thesis on why algorithmic bias is structural rather than incidental. It gives leadership teams a shared vocabulary for the risk before they have to defend a hiring, credit, or pricing decision. He has built and deployed AI inside organisations where failure is expensive: NASA, Boeing, Airbus, the Bank of England, the UK Competition and Markets Authority. The reference points are operational, not theoretical. He led AI and data science at Digital Catapult, the UK government’s deep tech innovation centre. He has seen what separates the firms that move beyond pilots from the ones that stall. As a Founding Trustee of We and AI and a Senior Fellow at UCL, his independence on responsible AI is institutional, not positional. That matters when the audience needs a voice that does not sell the technology. Biography highlights Author, Rage Inside the Machine: The Prejudice of Algorithms and How to Stop the Internet Making Bigots of Us All (Bloomsbury Business). Shortlisted, UK Business Book Awards, Specialist category. Former Director of AI and Data Science, Digital Catapult. Senior Honorary Fellow, Computer Science Faculty, University College London. Co-founder, UCL Centre for Decision-Making Uncertainty. Founding Trustee, We and AI. Author of over 100 peer-reviewed papers in artificial intelligence, with a focus on evolutionary computation, knowledge representation, and machine learning. Applied AI work for NASA, Boeing, Airbus, BT, the European Union, the Bank of England, the UK Competition and Markets Authority, and US national laboratories. Biography The history of artificial intelligence is older than most boardrooms assume, and so are the design choices that made today’s models prone to bias. That is the argument running through Robert Smith’s work as a complexity scientist, and it is the reason serious organisations book him when they need an AI conversation that holds up under scrutiny. Smith spent more than three decades inside applied AI before the current wave of public attention. He built systems for NASA, Boeing, Airbus, BT, the Bank of England, the UK Competition and Markets Authority, the European Union, and US national laboratories at Los Alamos and Oak Ridge. He went on to lead AI and data science at Digital Catapult, the UK’s deep tech innovation centre, where the question shifted from research to deployment at scale. His book Rage Inside the Machine, published by Bloomsbury Business and shortlisted for the UK Business Book Awards, traces algorithmic bias back through the intellectual history of computing. The case is technical, not rhetorical: apparently neutral data and models can encode prior injustice across hiring, credit, insurance, policing, and content moderation. He gives leadership audiences a way to interrogate their own systems without needing to read the code. Smith holds a PhD, is a Fellow of the Royal Society of Arts, a Senior Honorary Fellow at UCL Computer Science where he co-founded the Centre for Decision-Making Uncertainty, and a Founding Trustee of We and AI. He has more than 100 peer-reviewed papers to his name and has presented at Google, the UK Financial Conduct Authority, and corporate, academic, and policy venues internationally. Key speaking topics Artificial intelligence and generative AI AI ethics and responsible technology Algorithmic bias and governance Digital transformation Data analytics Future of technology Risk management Ideal for Boards and executive committees signing off on enterprise AI strategy CTOs, CIOs, Chief Data Officers, and heads of AI looking for a credible external voice on governance and bias Risk, compliance, and regulatory leaders in financial services, insurance, healthcare, and public sector Senior HR and people leaders deploying AI in hiring, performance, or workforce decisions Audience outcomes A clearer view of where bias actually originates inside their AI systems, with examples drawn from peer-reviewed research and operational deployments. A working language for board-level conversations about AI risk, beyond the vendor pitch and the headline. Specific questions executives can put to their data science teams and external suppliers to test whether claims about model behaviour are defensible. A grounded sense of where AI is genuinely creating value in regulated environments, and where it is creating exposure. A perspective on responsible AI that comes from a working scientist and trustee of an independent charity, not from a platform vendor.