📋 Tender Overview
The European Commission has published the final report of the Mutual Learning Exercise on National Policies for Artificial Intelligence in Science.Artificial Intelligence (AI) promises to accelerate the pace of scientific discovery and revolutionise how we uncover and use new knowledge. Future AI systems will become ever more powerful and accessible. To stay competitive, Europe must act: AI in science needs strategic, coordinated policies. Eleven countries joined the Mutual Learning Exercise (MLE) under the ECs Policy Support Facility (PSF) to share experiences and identify key levers across funding, infrastructure, and talent. The MLE highlighted the need for adaptive, long-term policy frameworks that combine top-down investment with bottom-up experimentation. Human and technical infrastructure, ethical governance, and open, FAIR data are needed to enable responsible, widespread adoption of AI in scientific research. The resulting set of recommendations for national policy makers and research organisation offers a flexible policy menu tailored to different stages of AI maturity in science. The recommendations address key challenges identified in the MLE country visits such as limited access to high-performance computing (HPC) and data infrastructure, fragmented and underused scientific data, and persistent talent gaps. The recommendations can be further tailored to countries stage of AI maturity in science (emerging, expanding, advanced).
