Assessing The Potential Savings of Artificial Intelligence in Education: Scenarios, Models and Redistribution Issues
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Abstract
Artificial intelligence (AI) is rapidly transforming education systems, but its economic effects remain largely unexplored. While the literature focuses mainly on pedagogical, ethical and social issues, few studies seek to estimate the potential efficiency gains associated with its integration. This article proposes an analytical and forward-looking framework for quantifying the possible economic effects of the thoughtful use of AI in education.Three scenarios are analysed: (A) AI ignored, (B) human substitution, and (C) augmented human action — a cobotic approach in which AI supports human capabilities. Based on a documentary analysis and a multi-level economic model (Quebec, Canada, OECD) focused on scenario C, the study estimates that 25 to 30% of educational tasks could be partially automated, generating efficiency gains equivalent to 5 to 8% of total education expenditure, or up to US$496 billion across the OECD.These results open up a discussion on the redistribution of the benefits of AI: reinvestment in educational services, staff training and ethical oversight of technologies. The article thus proposes that AI be considered as a public infrastructure whose gains must be governed in order to strengthen the quality and equity of education systems.
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