Federal AI Spending Surges 966% as Leadership Shifts From Governance to Execution

Federal spending on artificial intelligence contracts has exploded, with obligated funds increasing 966% between 2024 and 2026—from $355 million to $7.2 billion. The value of potential awards grew even faster, jumping 1,912% to reach $91.8 billion, according to new research from the Brookings Institution.

The number of federal agencies with AI contracts expanded from 17 in 2022 to 28 in 2026, spanning 441 total agencies. While the Department of Defense dominates spending at $90 billion, agencies from Commerce ($197 million) to the National Archives ($110,000) are now procuring AI capabilities. Total contracts across government tripled from 472 in 2022 to 1,743 in 2026.

Two Models of AI Governance

The Biden administration created the Chief AI Officers Council (CAIOC) in 2024 to coordinate AI initiatives across agencies. But the council's composition and mandate have shifted dramatically under the Trump administration, reflecting fundamentally different approaches to federal AI adoption.

Brookings researchers analyzed the backgrounds of 17 Biden-era council members and nine current Trump-era members using Leadership Connect data, LinkedIn profiles, and government websites. The contrast is stark: 89% of Trump council members came from prior government positions, compared to just 19% under Biden.

The Biden model emphasized what researchers call "governance-led adoption"—advancing AI through structured risk management, use-case inventories, and safeguards for systems affecting rights and safety. The council drew from diverse backgrounds in policy, science, health, budget, and legal fields.

The Trump approach represents "adoption-led governance," prioritizing rapid deployment and U.S. competitiveness, particularly against China. The current council concentrates expertise in cybersecurity, chief information officer roles, data operations, and enterprise execution—backgrounds suited to overcoming implementation barriers rather than designing oversight frameworks.

Why it matters

This shift changes how federal AI leaders are evaluated and how agencies coordinate. Under Biden, chief AI officers were valued for building governance processes and managing institutional legitimacy. Under Trump, they're judged on delivery—moving systems into operation and demonstrating tangible mission value. Risk management hasn't disappeared, but it now functions as a guardrail within a deployment agenda rather than a central organizing principle.

The operational focus may accelerate AI adoption in agencies with strong technical capacity and clear use cases, as evidenced by Defense Department spending. But it also risks widening capability gaps across government. Some agencies may advance quickly while others lag, creating uneven implementation across missions that serve different populations.

Execution Over Process

The governance-oriented Biden council emphasized standardization—common language, parallel movement across agencies, and process-heavy assurance. The Trump council appears designed for differentiated implementation, where agencies move at speeds determined by mission need and technical readiness rather than uniform policy requirements.

This shift is visible in federal spending patterns, which have moved from strategic planning toward operational contracts. The council's role becomes less about setting governance consensus and more about spreading usable practices and reducing capacity gaps between high-performing and struggling agencies.

With global AI spending projected to reach $2.5 trillion in 2026 and $3.3 trillion in 2027, the federal government's approach to coordination will shape not just how agencies adopt AI but which agencies succeed in deployment. The Trump-era CAIOC is still organizing but faces significant work ahead as federal AI spending continues its explosive growth.

These findings were first reported by the Brookings Institution in their analysis of federal AI policy and leadership.