Choose the simplest approach you can verify
Automation does not have to use AI. A rule can route a request using a known account code, check required fields or calculate a total from validated numbers. These steps can be easier to explain and test with conventional software.
AI may be useful when the input needs interpretation: varied email wording, documents with different layouts or a draft summary. Its output still needs checks appropriate to the consequences of an error. Choosing a model is not a substitute for designing the surrounding process.
Compare the job, not the labels
| Situation | Useful starting approach | Check before release |
|---|---|---|
| Stable, structured input | Rules or an existing integration | Required fields, valid codes and duplicate handling. |
| Variable documents or free text | AI-assisted extraction or interpretation | Representative examples, uncertainty and human correction. |
| Exact arithmetic or posting | Deterministic calculations and explicit rules | Reconciliation, access controls and approval. |
| Consequential or ambiguous decision | Employee decision with supporting information | Accountability, policy and an override route. |
Combine approaches when the workflow needs it
Consider a fictional inbox workflow. An AI component proposes a document category and extracts candidate fields. Conventional validation checks mandatory fields, known identifiers and arithmetic. An employee reviews uncertain values and approves any consequential action. This is an illustrative design, not a claim about a client deployment.
Keep the original input available to the reviewer. A plausible-looking result should not bypass the checks that an ordinary manual process requires. Missing fields should create a visible exception rather than a silent default.
Test before claiming a result
Do not infer production accuracy or return on investment from a short demonstration. Where a workflow cannot be tested safely, restrict the first phase to draft outputs and a review queue.
- Agree representative cases, including malformed, duplicate and incomplete inputs.
- Define acceptable outputs and which failures must stop processing.
- Check access boundaries and what information leaves each system.
- Measure review effort as well as automated handling time.
- Name an owner for alerts, changed interfaces, model updates and rollback.
Questions to ask before buying
Ask why a step needs AI, whether a rule or existing feature could do the job, how mistakes will be detected and how someone will override the result. Ask what happens if the external service is unavailable and who pays for ongoing usage and maintenance.
A bounded assessment can compare these options before an implementation is designed. The useful outcome is an informed decision, including the decision to keep a step manual.