Agentic artificial intelligence, which can operate autonomously with minimal human oversight, is advancing rapidly, raising critical questions about governance and global security, according to experts at the Special Competitive Studies Project (SCSP), a nonprofit and nonpartisan initiative focused on strengthening America’s long-term competitiveness in AI.
Unlike current AI systems that respond to prompts, agentic AI can independently set goals, create plans, and execute multi-step tasks. “AI is beginning to help build better AI,” the SCSP experts note. Ylli Bajraktari, president of the SCSP, warned in a recent newsletter that a self-accelerating loop where AI capability improves and development compounds could cause capability growth to far outrun projections.
Bajraktari emphasized the security implications: “An agent that can navigate complex bureaucratic systems, identify exploitable vulnerabilities, and act without leaving a clear attribution trail represents a qualitative expansion of adversarial capability.” He cautioned that adversaries are likely to deploy agentic AI systems in areas where governance is weakest, using them for coercion, espionage, and influence operations.
Effective governance, however, does not focus on the AI model itself but on the “scaffolding” built around it, the 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; permission structures defining system 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 areas, according to SCSP. First, responsibility is untraceable—there is no way to determine who authorized an AI agent’s actions. Second, current frameworks only assess whether a task was completed, not whether it was performed safely or caused harm. Third, agentic AI builds personal profiles that may accumulate sensitive data on behavior patterns, preferences, and inferences without user consent.
Despite these challenges, the SCSP experts assert that agentic AI is not a technology to be feared or deferred. Institutions that prioritize understanding, shaping, and governing agentic AI will not only determine their own competitive position but also influence the global environment in which such systems operate. For more insights, visit scsp.ai.
