What it means
Agent orchestration is the coordination of one or more AI agents, tools and process steps, deciding which component handles which task, in what order, and how results are combined and checked. It is usually handled by a control layer in the software rather than by the AI alone.
Real-world example
An insurer's claims system uses orchestration to route each incoming claim. One component extracts details from documents, another checks the policy, a third drafts a recommendation, and the orchestration layer decides when to stop and pass a case to a human, for example when documents are missing or the amount exceeds a threshold.
Why it matters for AI adoption
As AI systems grow more complex, orchestration determines reliability, cost and accountability. It is also where stop conditions, escalation rules and logging should be built in. Poorly orchestrated systems can loop, duplicate work or fail silently.
Questions to ask
- How does the system decide which component handles each step, and when to stop?
- Where are escalation rules to human staff defined, and who can change them?