A definitive forecast on the regulation of generative artificial intelligence for the years 2025 to 2035

Abstract

Generative artificial intelligence (AI) presents significant governance challenges due to its rapid technological advancement, emergent behavior, and the inability of existing regulatory institutions to keep pace with its development. This paper presents a qualitative, scenario-based forecast of the global regulation of generative AI between 2025 and 2035. Drawing on scenario planning, horizon scanning, and evidence from AI safety research, digital governance theory, and policy analytics, the study identifies two critical uncertainties shaping future regulatory outcomes: the level of international regulatory coordination and the pace of AI safety and interpretability advances. These uncertainties form the basis for two contrasting scenarios: Regulated Convergence, characterized by strengthened international cooperation, consolidated oversight institutions, and augmented governance supported by technical verification mechanisms; and Fragmented Acceleration, in which geopolitical competition, institutional fragmentation, and limited progress in AI safety hinder effective governance. The analysis evaluates the policy trade-offs associated with each scenario, including regulatory capacity, licensing regimes, transparency requirements, international coordination, and open-source AI development. The findings suggest that effective governance by 2035 will depend on sustained institutional investment, adaptive regulatory frameworks, technical advances in AI safety, and greater international collaboration. Without these conditions, fragmented governance is likely to remain the dominant trajectory, increasing regulatory gaps and societal risks associated with frontier AI systems.