Theory of Change

Our research provides insight to help us navigate the AI transition. We take the transformative impact of AI seriously, and work with large, state-of-the-art tools to provide rigorous empirical answers to questions such as how AI is changing the job prospects of early-career workers, which jobs and occupations win and lose, and how valuable AI capability improvements are to society. The overarching goal is to help firms, policymakers and the public  understand how to guide society to better futures.

Impact

Our research has been consistently widely discussed in mass-market and specialist media  including the Financial Times (here, here and here), The Economist, Bloomberg, Reuters, The Guardian, The Independent, Forbes and the Frankfurter Allgemeine Zeitung, among many others, giving the programme unusual reach across academic research, corporate strategy, policy formation, and the wider public debate.

Our research has developed a track record of moving rapidly from original empirical and policy work into government, corporate, and public decision-making. Our work on AI and labour markets has been cited in Microsoft’s New Future of Work Report, the International AI Safety Report, parliamentary research on AI and employment, the Skills England Annual Skills Report, the Greater London Authority’s economic outlook, the Hong Kong Economic Policy Green Paper, and major policy analyses from King’s Policy Institute, the International Center for Law and Economics, Demos and the Joseph Rowntree Foundation, and Wirtschaftsdienst, while also forming part of formal parliamentary evidence and being presented directly to senior government officials, cabinet-level ministers and central bankers. 

Our work on measuring emerging automation capabilities has informed advice on civil-service restructuring and policy discussions at the Hoover Institution, while our broader framework for governing AI through insurance, auditing, procurement, and due diligence has entered the professional-assurance and corporate-governance literature through the Ada Lovelace Institute, the AI Risk Institute, and subsequent work on global AI-governance architectures, insurance-based regulation, and AI cap-and-trade mechanisms; it has also been taught in the University of Chicago’s Economics of Transformative AI curriculum, delivered as a lecture at George Mason University, and circulated within Google DeepMind policy networks. 

Team

Philip Tomei, Research Director
Bouke Klein Teeselink, Senior Research Fellow
Jacob Schaal, Research Fellow

Selected Papers and Research

Klein Teeselink, B. (2025). Generative AI Exposure and Labour Market Outcomes: Evidence from the United Kingdom. Working paper. SSRN

Klein Teeselink, B., & Carey, D. (2026). AI, Automation, and Expertise. Working paper. SSRN

Klein Teeselink, B., & Tomei, P. (2026). What Jobs Can AI Learn? Measuring Exposure by Reinforcement Learning. Working paper. SSRN

Chandar, B., & Klein Teeselink, B. (2026). How Does AI Change Labor Demand? Evidence from 41 Countries. Working paper. Stanford Digital Economy Lab

Vossos, A., Andronic, A., Klein Teeselink, B., & Akileswaran, K. (2026). Artificial Intelligence and the Future Supply of Skills: Evidence from UK University Applications. Working paper. SSRN

Tomei, P. M., Jain, R., & Franklin, M. (2025). AI Governance through Markets. arXiv. Paper

Tomei, P. M. Machina Economica, Part One: Autonomous Economic Agents in Capital Markets. AI Objectives Institute. Essay

Tomei, P. M. Machina Economica, Part Two: The Commodification of Risk. AI Objectives Institute. Essay

The Diffusion Dilemma. Arena. Essay