[2604.06215] Governing frontier general-purpose AI in the public sector: adaptive risk management and policy capacity under uncertainty through 2030

Computer Science > Computers and Society arXiv:2604.06215 (cs) [Submitted on 16 Mar 2026] Title:Governing frontier general-purpose AI in the public sector: adaptive risk management and policy capacity under uncertainty through 2030 Authors:Fabio Correa Xavier View a PDF of the paper titled Governing frontier general-purpose AI in the public sector: adaptive risk management and policy capacity under uncertainty through 2030, by Fabio Correa Xavier View PDF Abstract:The governance of frontier general-purpose artificial intelligence has become a public-sector problem of institutional design, not merely a technical issue of model performance. Recent evidence indicates that AI capabilities are advancing rapidly, though unevenly, while knowledge about harms, safeguards, and effective interventions remains partial and lagged. This combination creates a difficult policy condition: governments must decide under uncertainty, across multiple plausible trajectories of progress through 2030, and in environments where adoption outcomes depend on organizational routines, data arrangements, accountability structures, and public values. This article argues that public governance for frontier AI should be based on adaptive risk management, scenario-aware regulation, and sociotechnical transformation rather than static compliance models. Drawing on the International AI Safety Report 2026, OECD foresight and policy documents, and recent scholarship in digital government, the article first rec...