A fixed workflow follows defined steps. An AI agent has more freedom to decide which steps or tools to use. Neither approach is automatically better: the right choice depends on how predictable the work is and how costly a mistake would be.
Start with a repeatable example
Consider a supplier enquiry. Checking required fields and routing the enquiry by category can follow explicit rules. Interpreting an unfamiliar technical attachment may benefit from an AI-assisted analysis. Approving a commercial commitment should still follow the business's approval rules.
This example suggests a mixed system: predictable routing, bounded assistance and a human decision where necessary. It does not require giving an agent permission to run the entire purchasing process.
Compare the operating requirements
Write down the decisions the system must make. For each decision, ask whether the valid outcomes can be listed in advance. Next, specify the tools it may use, the information it may access and the actions that require confirmation.
- Prefer a fixed workflow when the sequence and validation rules are stable.
- Consider agent behaviour when choosing the next step is part of the problem.
- Require a stop condition when the system is uncertain, exceeds its budget or repeatedly fails.
- Keep a record of actions so the operator can understand what happened.
Commission a fair comparison
Give a specialist the same representative cases for both approaches. Compare completion quality, intervention time, latency and operating cost. Include a case with missing information and one with a connected service unavailable.
Ask for a recommendation that explains the trade-off, rather than a demo that merely looks autonomous. You should be able to identify who is accountable for each external action.
Anthropic's guide to effective agents explains the workflow-versus-agent distinction. Use it as background, then post a scoped automation project with your actual decision points.