Google expands its AI & Economy team with Nobel laureate Philippe Aghion and two new research directors

Google announced in an official blog post that it is expanding its AI & Economy Research Program and bringing in world-class economists to help build and lead the work. The post is bylined by Scott Strand, head of StratOps and special projects for Technology & Society, and Zanna Iscenko, AI & Economy lead in the Chief Economist's Office. The program previously launched AI & Economy ATLAS v1.0 and an interactive open-access site to understand how people are using Google's AI tools at work and in daily life.

Tracking adoption patterns is only the beginning, according to Google. Because AI is reshaping jobs, businesses and everyday life, the team argues that navigating the shift requires fine-grained data combined with rigorous economic inquiry, so that organizations, workers, researchers and policymakers can make sense of the transition. The program focuses on the future of work, productivity and growth, global technology diffusion, and AI's impact on scientific discovery.

On the academic side, Philippe Aghion joins as an academic advisor. A 2025 Nobel laureate in economics and the Kurt Björklund chaired professor at INSEAD and the Collège de France, he will apply his work on innovation-led growth and creative destruction to modeling AI's long-term macroeconomic trajectory, working alongside existing advisors and fellow laureate Michael Spence and Cambridge's Dame Diane Coyle.

Professor Ajay Agrawal of the University of Toronto's Rotman School of Management joins the visiting fellows program, where he will collaborate with David Autor, a current fellow and head of MIT's Department of Economics. Google says his research will advance core work on the economics of AI and scientific discovery, AI and robotics, and how AI can expand the frontier of human welfare.

To steer empirical projects, Google is introducing two directors. Anu Madgavkar joins from the McKinsey Global Institute, where she spent two decades leading global research on labor markets, technology adoption and structural economic transitions, and has advised governments, multilateral institutions and business leaders as well as contributing to the World Economic Forum and the United Nations. At Google she will lead empirical research on global AI diffusion, small business ecosystems and the workforce impacts of generative AI. Daniel Rock also joins as a director of the research program, tasked with driving empirical projects and integrating insights across the agenda.

What makes the expansion notable is timing. The question of how AI affects employment and growth is moving from academic argument toward a phase that needs long-run measured data. Google frames the program as measuring and analyzing that evolution in real time rather than through retrospective statistics, and it points readers to ai.google/economy for the underlying research and data that are meant to inform businesses, workers and policymakers.

What to watch next is whether a structure of academic advisors, visiting fellows and program directors produces results that can be checked and cited in policy debate, whether open datasets such as ATLAS keep widening their coverage, and whether the findings actually reach workforce training programs and industrial policy decisions.