Nearly half of agentic AI projects may not survive to 2027 — here's why

Industry forecasts this year put the agentic AI project cancellation rate at close to 40% by the end of 2027. The three reasons cited most consistently: escalating costs, unclear business value, and inadequate risk controls.

None of those three are technology failures. They're scoping failures — the kind that show up when a project starts from "we should have an AI agent" instead of "we have this one costly problem, and an agent might solve it."

Escalating costs usually mean the project grew past its original scope without anyone re-checking whether the value grew with it. Unclear business value usually means there was never a single number the team agreed to measure in the first place. Inadequate risk controls usually mean the agent was given more autonomy than anyone actually verified it could handle safely.

All three are avoidable with the same discipline: start narrow, name the one metric that proves it worked, and only expand scope once that's actually true. It's a less exciting pitch than "transform your business with AI," but it's the version that's still running in 2027.