CSIS: Agentic AI Definition Confusion Undermines Governance

The absence of a standardized definition for Agentic AI is undermining testing, procurement, and governance frameworks across the United States, particularly within national security sectors, according to a new report from the Center for Strategic and International Studies (CSIS). The report underscores that definitional fragmentation, largely originating from the industry itself, compels a fundamental shift from purely technical controls to a relational governance model integrating human, technological, and institutional contexts.

CSIS analysis reveals that this lack of unity leads to misaligned processes, where different federal agencies apply inconsistent benchmarks for evaluating and procuring autonomous systems. The report specifically points to the inadequacy of current technical testing standards, which fail to capture the systemic risks posed by adaptive AI agents operating in complex, contested environments.

To address these shortcomings, the report advocates for the adoption of a relational perspective—one that views Agentic AI not as an isolated tool, but as an entity enmeshed in a triadic relationship between technology, human operators, and institutional protocols. This approach demands a move from technical control to systemic governance, establishing contextual frameworks that dynamically adjust definitions based on operational scenarios, from military command centers to civilian infrastructure.