Enterprises struggle to assign ownership for multi-agent AI outputs

As enterprises deploy growing numbers of multi-agent AI systems, organizations face significant governance and liability challenges when agent workflows fail. The author argues that accountability must be assigned to a named human rather than a system, handoffs between agents require careful design and logging, and robust audit trails recording the reasoning chain are essential for preventing compliance failures. Open article →