On 3 April 2025, the White House issued OMB Memorandum M-25-21, directing every major federal agency to appoint a Chief AI Officer, expand the use of artificial intelligence across government operations, and manage risk proportional to each system’s impact on citizens. Twelve months later, the Federal Agency AI Use Case Inventory records 3,611 AI use cases across 56 agencies, more than double the prior year’s total. A May 2026 survey of more than 200 technology executives across civilian and defence agencies found 53% are actively planning agentic AI pilots. Only 8% of those agencies have incident response frameworks in place.
This is the eleventh piece in the Pre-Mortem series. Five questions, applied to the public record, before a programme has had the chance to succeed or fail.
The Bet
The US government is betting that embedding AI across 3,611 federal workflows covering benefits decisions, immigration adjudications, healthcare determinations, and law enforcement, will make government faster and more efficient before the accountability architecture governing those decisions is clarified. OMB M-25-21 requires Chief AI Officers, public AI inventories, and risk management proportional to impact. The hard compliance deadline for role-specific AI training arrives in September 2026. If that architecture catches up to the deployment before a consequential wrong decision reaches a citizen with no named relief, the bet holds.
The Assumption
The expansion’s credibility turns on one unanswered question: whether the Federal Tort Claims Act, designed to govern negligent acts by human federal employees, applies without amendment to decisions made by AI agents running inside federal systems. The same May 2026 survey found only 44% of agencies include vendor liability clauses in AI contracts, and only 29% have documented kill-switch procedures. The legal architecture governing accountability in federal government was designed for humans acting on behalf of the state. No court has ruled on whether it extends to the agents they built.
The Sequence
In 2024, federal agencies reported 1,757 AI use cases. By 2025, that figure had grown to 3,611. In March 2026, the Department of Veterans Affairs expanded AI use in claims processing, with 215 of its 367 AI systems classified as high-impact, covering benefit eligibility, healthcare access, and fraud detection. In May 2026, the majority of agencies were planning agentic pilots, with only 20% having defined pre-deployment testing policies. The AI reached citizens before the accountability reached the AI.
The Pager
Russell Vought, Director of the Office of Management and Budget, carries the M-25-21 mandate at the centre of the federal AI expansion. Every covered agency has designated a Chief AI Officer responsible for inventory, risk management, and AI governance at agency level. The VA alone runs 215 high-impact AI systems. No single published document names what relief is available to a veteran whose claim was influenced by one of those systems, which official carries accountability for that decision, or whether the Federal Tort Claims Act applies when the acting party is software, not a civil servant.
The Proof
The measure that would settle this is a published legal standard: a named accountability chain clarifying who carries liability when a federal AI agent makes a consequential wrong decision, whether government, vendor, or joint, and whether the Federal Tort Claims Act applies or new legislation is required. No such standard has been published. OMB M-25-21 requires risk management proportional to impact. It does not name the relief available to a citizen when that risk management fails, nor the date by which that question must be answered.
Verdict
If OMB publishes, before the September 2026 training compliance deadline, a named accountability standard for AI-driven decisions in high-impact federal systems, covering who carries liability when the AI is wrong and what legal remedy a citizen holds, the expansion will stand as the most deliberate attempt the US federal government has made to govern AI before it reaches citizens at scale. Without that, the US government has put AI into 3,611 workflows and left the question of who carries the call when the AI gets it wrong to be answered in court, by accident, or not at all.