AI Systems, Markets & Governance

AI is reshaping our societies and economies at unprecedented speed. This creates an evidence dilemma for policymakers: separating hype from real trends while designing governance that manages real risks and preserves competitive advantage in a global race for AI leadership. Interface’s AI Systems, Markets & Governance Programme examines how technical capabilities, market forces, and governance frameworks interact to shape AI development in Europe and globally – analyzing what AI can do, how companies compete to build it, how capital flows shape priorities, and how policy choices influence outcomes.

Our research provides the empirical foundation for evidence-based governance by integrating technical assessment, market analysis, and policy evaluation. Through rigorous analysis, including quantitative methods, comparative policy research, and expert consultation, we examine how AI systems perform in practice, how market structure influences innovation trajectories, and how regulatory approaches affect both competitiveness and safety outcomes. This allows us to contextualize industry narratives, critically examine claims where necessary, and adapt insights for Europe's policy realities.

2026 Research Priorities:

• European AI ecosystem analysis: Map startup and investment landscapes across Europe and the United States through analysis of startup profiles, investment patterns, and market concentration. Investigate divergent ecosystem dynamics and identify emerging technological niches and funding gaps.

• AI capability assessment: Evaluate claims about frontier AI capabilities in economically significant domains such as software development, examining the gap between benchmark performance and real-world deployment. Critically assess how current evaluation methodologies inform policy decisions and whether they capture what matters for governance.

• Governance translation: Synthesize technical research on AI safety and evaluation methodologies for policymakers and practitioners. Translate emerging findings on capability assessment and risk management into actionable guidance for designing effective governance frameworks that account for both technical realities and competitive dynamics.