A new report from the Government Accountability Office arrives at a moment when federal AI spending is accelerating faster than the institutional frameworks meant to govern it. Released April 13, 2026, GAO-26-107859 examines how four major agencies—the Department of Defense, the Department of Homeland Security, the General Services Administration, and the Department of Veterans Affairs—have been acquiring AI capabilities, and finds a consistent pattern: agencies are learning hard lessons in isolation, then failing to share what they’ve learned.

The GAO’s April 2026 report on federal AI acquisitions (GAO-26-107859) is valuable not just for its top-line findings but for the taxonomy it provides of where government AI procurement consistently breaks down. Based on interviews with officials at DOD, DHS, GSA, VA, and the Department of Commerce, the report identifies six challenge areas—three strategic and three programmatic—that recurred across agencies regardless of the specific AI capability being acquired.

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There is a specific and fixable failure running through federal AI procurement that GAO’s April 2026 report (GAO-26-107859) surfaces with unusual clarity: agencies are accumulating experience with AI acquisitions and then letting that experience evaporate.

The pattern shows up in concrete cases. VA’s SoKAT program—a natural language processing tool built to scan veterans’ survey responses for indicators of suicidal ideation—was retired in January 2023 after officials concluded it didn’t improve enough over existing solutions to justify the cost. No lessons were documented. VA has multiple other AI programs targeting suicide prevention among veterans. Those programs could have benefited from what SoKAT’s team learned. They didn’t, because it was never written down.