Workflow or AI agent? Choose the simplest approach that works

Start with variation in the work

A traditional workflow fits known inputs, fixed rules and predictable exceptions. An agent becomes relevant when the route depends on unstructured information, intermediate findings or several possible tools.

Compare controllability

A fixed flow can be tested and audited step by step. An agent chooses dynamically and therefore needs boundaries, evaluations and trajectory observation. Do not choose an agent when a decision tree solves the problem clearly and cheaply.

Separate deciding from executing

A model can classify or propose while a deterministic workflow performs the allowed action. This hybrid form keeps transactions predictable and uses interpretation where it adds value.

Place human control around impact

Not every step needs approval. Involve a person for irreversible actions, low confidence, financial or legal consequences and communication that commits the organisation. Make escalation simple and visible.

No. An agent plans or selects actions with tools; a chatbot may only provide text responses.

Design for failure

Decide what happens with missing data, tool outages, conflicting sources and repeated attempts. Use idempotent actions, limits and a manual queue instead of retrying without a bound.

Start with a measurable pilot

Compare task outcome, lead time, rework and operating burden. Scale only when failures are understood, an owner can intervene and automation demonstrably improves on the current process.

if steps_are_known and exceptions_are_bounded: choose_workflow() else: evaluate_agent_with_human_review()

Make choose a workflow or AI agent verifiable

The decision review for choose a workflow or AI agent first focuses on one existing process that separates fixed steps, decision latitude, exceptions and required human approval. Define the acceptable user outcome, essential inputs and authorised approver for choose a workflow or AI agent before the trial starts. Keep the first choose a workflow or AI agent trial small enough to separate causes from effects.

Build evidence for choose a workflow or AI agent around one realistic successful route and also simulate an agent used for fully predictable work, a rigid flow used for ambiguity and a missing escalation route. For every choose a workflow or AI agent check, record the expected outcome, visible evidence and recovery action when it fails. The final decision question for choose a workflow or AI agent is: “Is a chatbot automatically an agent?”

choose a workflow or AI agent: from trial to everyday operation

Assign choose a workflow or AI agent one operational owner, one subject reviewer and a clear fallback route. Treat the choose a workflow or AI agent checklist as separate evidenced steps, so punctuation or phrasing never becomes part of the process logic. Ask the relevant user to complete choose a workflow or AI agent without spoken help and record every point that still needs explanation or manual recovery.

Keep change rights, logging, support and review dates for choose a workflow or AI agent in one operating plan. Repeat the choose a workflow or AI agent trial after a change to source data, configuration, model, integration or user role. Expand choose a workflow or AI agent only when the team can also detect, contain and recover an agent used for fully predictable work, a rigid flow used for ambiguity and a missing escalation route.

Stop the choose a workflow or AI agent rollout while an agent used for fully predictable work, a rigid flow used for ambiguity and a missing escalation route is not reported visibly and recoverable by the assigned owner.