Library insight
Agentic use cases: similar value, harder to deliver
2.48 vs 3.41
What you see
Of the 4,980 use cases in the MetroMinds Library, 600 are agentic. They score almost the same on business value as the other 4,380 (3.88 against 3.81), but much lower on feasibility (2.48 against 3.41) and higher on risk (4.06 against 3.79).
Why it matters
Agents promise roughly the same value as other AI, but they are harder to deliver and carry more risk while you do it. Almost a third of agentic use cases, 190 of 600, have the lowest possible feasibility score.
What you can do
Before you approve an agent, ask whether the work needs a goal managed over several steps and several tools, and which actions the agent may take alone. If an assistant or an automated workflow delivers most of the value, choose that. The full article adds a readiness check.
