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Framework conditions and funding for AI in science Mutual learning exercise on national policies for AI in science : first thematic report
Paper Details
Published: 2025/04/30
DOI: 10.2777/7211107
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HTMLThe Mutual Learning Exercise (MLE) on National Policies for Artificial Intelligence (AI) in Science provides a forum for Member States and Associated Countries of Horizon Europe to share operational and policy approaches to advance the adoption of AI in science. Building on previous discussions about infrastructure and talent, this report focuses on funding and framework conditions for AI in science. Drawing from discussions at the MLE workshop in Belgium on 20-21 March 2025, a survey of national policymakers, and desk-based research, this report explores funding, governance, and institutional support models for AI in science from across Europe. It identifies different types of funding frameworks and considers what lessons successful AI in science initiatives offer for the design of funding interventions. It then considers the research governance challenges emerging from AI adoption in science. It concludes by reviewing the diverse policy levers that play a role in enabling AI in science. Across these areas, the report proposes recommendations to support AI adoption in science. Thanks are due to the participants in these evidence-collection activities for sharing insights to inform this document.
