- GAO has introduced a framework to assess U.S. AI competitiveness
- The framework examines science, workforce, governance and economy
- The 2026 FedCiv Summit will discuss scaling AI across government
The Government Accountability Office has released a framework designed to help analysts and policymakers assess U.S. competitiveness in artificial intelligence and identify policy options to improve the country’s standing in the global AI landscape.
As federal agencies continue to advance AI adoption and shape related policy priorities, government and industry leaders will further discuss the technology’s role in civilian missions at the Potomac Officers Club’s 2026 FedCiv Summit on Oct. 29. The event will feature executive-level discussions on scaling AI across government, cloud and data infrastructure, cybersecurity, and cross-agency initiatives shaping procurement and partnership decisions. Book your spot now!
GAO said Thursday the framework outlines a method for evaluating U.S. AI capabilities, capacity and competitiveness compared with other countries. It could also help analysts provide policymakers with structured information about AI competitiveness.
In September, GAO identified 94 governmentwide requirements related to federal artificial intelligence adoption and said 10 executive branch oversight groups have been created to supervise the government’s use of AI.
What Are the Framework’s Key Pillars?
GAO organized the framework into four pillars: science and technology, human capital, governance and economy.
The science and technology pillar includes research and development, software, hardware, data and digital infrastructure. Human capital encompasses the workforce, education and human capital mobility.
The governance category addresses collaboration and partnerships, laws and policies, responsible practices, and vision and leadership. The economy pillar focuses on business environment, investment and financing, and business activities.
The congressional watchdog said analysts can use the pillars and subpillars to evaluate factors affecting U.S. AI capabilities and capacity relative to other countries.
How Does the Framework Work?
According to GAO, the framework includes four steps for conducting assessments.
The first step focuses the assessment by selecting targeted AI competitiveness outcomes. The second step identifies indicators for measurement or evaluation.
The third step involves conducting data analysis using selected indicators and data sources. The fourth step develops policy options and a final product based on the findings.
The agency said the framework could support multiple policymaker needs, including evaluating the progress of the U.S. and peer nations toward AI competitiveness outcomes.
