The rise of agentic artificial intelligence—systems that can operate autonomously with minimal human oversight—is reshaping the landscape of national security and global competition, according to experts at the Special Competitive Studies Project (SCSP), a nonprofit and nonpartisan initiative focused on strengthening America's long-term AI competitiveness.
Unlike existing AI that generates responses to prompts, agentic AI can independently set goals, create plans, and execute multi-step tasks. As Ylli Bajraktari, president of SCSP, noted in a recent newsletter, this technology could create a self-accelerating loop where AI capability improves and AI development compounds, causing the pace of capability development to far outrun projections.
Bajraktari warned that agentic AI represents a qualitative expansion of adversarial capability. An agent that can navigate complex bureaucratic systems, identify exploitable vulnerabilities, and act without leaving a clear attribution trail could be deployed by adversaries in areas where governance is weakest, potentially for coercion, espionage, and influence operations.
Effective governance of agentic AI, contrary to what many policymakers might think, involves not just the AI model itself but the scaffolding built around it, SCSP experts explained. This scaffolding includes connectors to bridge the model to real-world infrastructure such as email, booking systems, and financial platforms; memory that allows the system to learn and adapt over time; planning capabilities to break large objectives into smaller tasks and navigate obstacles; permission structures defining what the system can access; and guardrails determining what the system will refuse to do, such as spending limits or human sign-offs.
Accountability remains a major challenge, with governance falling short in three key ways. First, responsibility is untraceable when using AI—there is no way to determine who authorized what if an agent acts on your behalf. Second, current frameworks don't ask whether an AI agent performed a task safely or caused harm, only that the task was completed. Third, agentic AI builds personal profiles that may include more sensitive data than individuals want, by accumulating information on patterns of behavior, preferences, and inferences.
Despite these challenges, SCSP experts emphasize that agentic AI is not a technology to be feared or deferred. Institutions that prioritize understanding, shaping, and governing agentic AI will determine their own competitive position and also impact the character of the environment in which agentic AI operates globally. For more information on how the United States should pursue effective governance of agentic AI, visit scsp.ai.
