The presentation will focus on the expected macroeconomic productivity gains from Artificial Intelligence (AI) over a 10-year horizon in OECD and G20 economies. It relies on a micro-to-macro framework by combining existing estimates of micro-level performance gains with evidence on the exposure of activities to AI and likely future adoption rates, feeding into a general equilibrium multi-sector model to aggregate the impacts. In the baseline scenario, where AI diffuses at a similar pace that was observed for previous digital technologies such as computers and the internet, the paper finds that AI-driven productivity gains are expected to raise labour productivity and per capita real income growth by about 0.6 percentage points on average. However, the gains vary widely across the OECD, in a range of 0.1–0.95 percentage points, with stronger specialisation in highly AI-exposed knowledge intensive services such as finance and ICT services and more widespread adoption key to higher gains. It is based on a series of papers with colleagues Francesco Filippucci, Katharina Laengle, Matthias Schief (OECD) and Muhammed Yildirim (Harvard Growth Lab).
About the speaker
Peter Gal is Deputy Head of Division and Senior Economist in the Structural Policy Research Division of the Economics Department at the OECD. Over the past few years, he has led a team of economists examining the macroeconomic productivity implications of artificial intelligence. During his 15 years at the OECD, he has worked on both micro- and macroeconomic aspects of productivity, labour markets, and the role of structural policies, published in policy reports and academic journals. He previously worked at the IMF and the Central Bank of Hungary. He holds a PhD in Economics from the Tinbergen Institute (Amsterdam) and a Master’s degree in Economics from Corvinus University of Budapest.
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