US Government AI Adoption Faces Hurdles Despite Increased Use

The United States government is increasing its use of artificial intelligence (AI), but hiring challenges and a risk-averse culture are slowing broader adoption. A new report from the Brookings Institution found that while AI integration has accelerated in the past three years, its use remains concentrated within a few large agencies.

Forty-one agencies reported using AI in 2025, documenting over 3,600 distinct projects. This represents a 69 percent increase from the previous year. In 2023, 21 agencies reported AI use. Many of these projects focus on streamlining operations and back-office processes. Others involve mission-oriented work such as benefits delivery, health services, and law enforcement.

Despite this growth, five agencies accounted for more than half of all AI use over the past three years. Large agencies, those with over 15,000 employees, made up more than three-quarters of all AI use in 2025. While smaller and midsize agencies are beginning to experiment with AI, larger agencies are expanding their efforts more aggressively.

Several factors impede wider adoption. These include workforce capacity constraints, funding challenges, and a lack of trust in AI's usefulness and safety. The federal government's slow hiring process and limited career advancement opportunities for technologists also present obstacles. Recent layoffs of federal workers may have further undermined efforts to recruit AI expertise.

A risk-averse culture within the federal government discourages experimentation and innovation. The inherent opaqueness of some AI processes can also erode trust, particularly for sensitive applications. The growing politicization of large language models (LLMs) also poses a challenge to adoption.

Recommendations to improve AI adoption include streamlining hiring for AI-related roles and creating new career paths for AI professionals. The report also suggests investing in AI literacy, documenting and sharing successful AI implementations, increasing transparency around AI use, and focusing AI investments on high-impact projects.