Fragmented control, collective risk: multi-agent AI and the coming governance crisis

Multi-agent artificial intelligence (MAAI) systems are increasingly deployed across economic and digital infrastructures. Existing regulatory frameworks, including the EU AI Act and related initiatives, largely focus on individual AI systems and are therefore poorly suited to govern risks that arise from agent interaction. This paper argues that multi-agent AI introduces distinct governance challenges, including emergent behavior, tacit coordination, cascading systemic risks, and difficulties in assigning accountability. Traditional risk management approaches, which rely on static and component-based analysis, are inadequate for adaptive, networked systems operating across jurisdictions.

Through a comparative review of policy developments in the European Union, United States, and Asia-Pacific region, the paper identifies a growing governance gap, alongside early regulatory experimentation such as China's emerging standards for intelligent agents. The paper concludes that effective oversight will require a shift from model-centric regulation toward system-level and adaptive governance frameworks capable of addressing the collective dynamics of multi-agent AI systems.