Maintaining leadership in the frontier AI race requires the United States to put its most advanced AI capabilities to work in the scientific, technological, and security missions where they create strategic advantage. Doing so requires evaluation that reduces uncertainty and provides the evidence needed to make informed investment, adoption, and policy decisions about how those capabilities can be used effectively.
Realizing the U.S. AI Advantage
U.S. leadership in frontier AI will translate into strategic advantage when advanced capabilities can be effectively deployed in the scientific, technological, economic, and security domains that matter most. New models can extend those capabilities to authorized users working in high-consequence environments, provided testing establishes the evidence, safeguards, and operating parameters necessary for their use.
A robust testing regime can accelerate the transition from frontier capability to real-world impact. It can identify where advanced models provide meaningful advantage, support decisions about access and deployment, establish appropriate operating limits, and verify performance as models are integrated into consequential missions.
What is needed is a boundary around evaluation. The evaluator provides the evidence. The evaluator does not make the ultimate policy choices or risk acceptance decisions, certify a model as universally safe, or replace the accountability of mission owners, users, developers, or government officials. If the global AI capability gap continues to narrow, the United States’ ability to effectively deploy its most advanced AI in consequential missions may become the critical source of strategic advantage.