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Automation vs agents — how we choose
Automation moves structured work through known steps. Agents decide and act within a job boundary using tools — often with a human approving sensitive writes. Many programmes need both: automation for the highway, agents for the junctions.
Commercial pages: AI automation → · AI agents →.
Choose automation when
- Steps are stable: validate → create record → notify → close.
- Exceptions are rare and can escalate to a queue.
- Determinism and cost per run matter more than flexible language reasoning.
- You already know the systems of record (CRM, ERP, forms).
Choose agents when
- The job needs interpretation across messy inputs (email, docs, tickets).
- Tool use varies by case — search, draft, compare, then propose a write.
- A person should approve before irreversible changes.
- You are combining retrieval (RAG →) with actions.
How we choose on real briefs
We map volume, exception rate, write risk and integration readiness. High-volume, low-ambiguity paths become automation. High-ambiguity, high-judgement paths become agent assists with oversight. Mixed programmes get a thin automation spine first, then agent skills where language earns its keep.
If the map is still fuzzy, start with Audit →. If the job is named, use Scope → or Process →.
Pitfalls
- Calling every chatbot an “agent”.
- Automating a broken process at higher speed.
- Agents without integrations — demos that cannot touch real systems.
- No stop conditions or audit trail on writes.
Not sure which shape fits?
Tell us the job, volume and systems. We will recommend automation, agents or both — then scope the first production slice.