As AI agents increasingly cooperate, compete, and make decisions across digital and economic infrastructures, their interactions raise difficult questions about control and responsibility. What happens when risks emerge from the collective behavior of multiple agents? And who is accountable when no single actor controls the outcome?
In her article published in AI Magazine, AEGIX AI Academy Director Caryn Lusinchi examines the growing gap between multi-agent AI capabilities and the frameworks intended to govern them. She argues that approaches focused on individual AI systems struggle to address risks arising from interactions between agents, including unexpected behavior, tacit coordination, and cascading failures.
Drawing on policy developments across the European Union, United States, and Asia-Pacific, Lusinchi calls for oversight that accounts for how interconnected systems behave and evolve. She identifies three practical mechanisms: public AI-agent registries, auditable records of agent-to-agent interactions, and cross-jurisdictional regulatory sandboxes.
The article makes a case for acting before systemic failures force a response, placing accountability and adaptive oversight at the center of multi-agent AI governance.
Read the full article in AI Magazine