Gartner's June 2025 forecast put more than 40 percent of agentic AI projects on track for cancellation by the end of 2027, naming escalating cost, unclear business value, and inadequate risk controls. None of those are model problems. The same analysis estimated that only about 130 of the thousands of vendors claiming agentic capability were building anything that deserved the label.

So, the useful question in a federal environment is no longer whether an agent can perform a task. It is whether the organization deploying it can say, precisely, what it may touch, how anyone would know if it went wrong, and who is accountable when it does. This paper answers those three.