Signal GovLab foresight study identifies seven convergent signals reshaping data governance in the AI era

Summary

The GovLab convened two expert forecasting studios in 2025 and 2026, bringing together 19 practitioners from multiple countries working in official statistics, digital trade policy, open science, AI governance, geospatial systems and public sector innovation. Using a qualitative signal scanning method rooted in horizon scanning and anticipatory governance traditions, the researchers drew out emerging developments in data access, governance and reuse, clustered and synthesized them, and tested them against practitioner experience. The result was seven convergent signals, including strain on the open data paradigm, a shift toward machine centric and AI mediated data ecosystems, and inference reshaping the foundations of data governance. The remaining signals cover growing difficulty sustaining data infrastructure, governance fragmenting across institutions and jurisdictions, a turn toward strategic control driven by sovereignty and security concerns, and data sharing models that need stronger incentive and benefit sharing mechanisms. The paper argues that data governance is becoming inseparable from AI governance, digital public infrastructure, economic strategy, democratic resilience and geopolitical competition. The authors frame the study not as a specific technological forecast but as an evidence informed diagnostic framework for reasoning about structural shifts already underway.