Some workflow steps do not need a long answer. They need a bounded decision: classify this case, route it to the right queue, or pick the next action.
That is the niche OpenAI is aiming at with the Decisions API. The service is generally available, built for questions with bounded answers, and designed to return typed answers from text, images, and JSON. OpenAI says it can be up to 10x faster than the Responses API for these cases.
The operational consequence is simple: if a process is waiting on a yes/no, a score, or a choice, a smaller decision layer can be easier to fit into production than a general-purpose chat step. Less latency helps. So does typing, because the result is a decision the workflow can trust, not a paragraph that still needs interpretation.
That does not mean every AI step should become a decision call. Bounded work is where the rules are clear and the output can be validated. If the task needs open-ended drafting, reasoning, or explanation, a broader model step still makes more sense. But where the system only needs to decide between known paths, the question is usually not “can AI do it?” It is “should this be a decision service or a conversation?”
For teams building routing, triage, or next-action logic, that distinction matters. It changes cost, review design, and how much software depends on human interpretation after the model responds.