ai@cam Annual Report 2025-2026

Abstract

In its third year, ai@cam has demonstrated that its model for AI innovation delivers tangible outcomes. By connecting world-leading research with real-world challenges across healthcare, local government, environmental sustainability, cultural heritage and scientific discovery, ai@cam is accelerating interdisciplinary research, translating ideas into public benefit, and strengthening Cambridge’s role as a national and international leader in AI that serves science, citizens, and society.

Executive Summary

ai@cam is the University of Cambridge’s mission for AI that serves science, citizens, and society. In 2025–26, the initiative supported 29 collaborative research and innovation projects, catalysed new spin-out companies, advanced AI into clinical practice and public services, trained over 750 researchers, and expanded partnerships across government, industry and international research networks. By providing the infrastructure for interdisciplinary collaboration, ai@cam is creating lasting capacity for AI innovation that delivers real-world impact.

Key Achievements 2025–26

• Worked with 10 local authority partners, alongside three central government departments and four national regulators
• Catalysed four spin-out companies from ai@cam-supported research
• Secured £180k in government funding for the Local Government AI Accelerator
• Helped AI-deas projects secure over £300k in follow-on funding while supporting more than £150m in funding bids
• Trained over 750 researchers through AI for Science and entrepreneurship programmes
• Supported 29 collaborative R&D projects across four core programmes
• Engaged over 2,500 people through major events, public dialogues and international workshops
• Established a University-wide AI community of practice involving more than 200 professional services staff across 90 departments

Looking forward

Our priorities for the coming year will include:

• Building Cambridge’s AI capabilities through training, entrepreneurship and interdisciplinary collaboration
• Expanding pathways from research to deployment through spin-outs, clinical translation and the AI Observatory
• Growing the Local Government AI Accelerator and strengthening collaboration with government and public sector partners
• Embedding public dialogue and policy engagement into the development and deployment of AI
• Scaling ai@cam’s innovation model to deliver long-term impact across research, public services and industry
• Securing long-term investment to strengthen the University’s capacity for AI that serves science, citizens, and society

Download the Full Report

The complete findings and details can be found in the full report.