When should a project use AI agents instead of fixed automation?
Use fixed automation when inputs and rules are predictable. Consider AI when the job involves varied documents, language, or choosing among steps. A combined workflow can apply fixed rules to record changes while using AI to prepare a recommendation.
Scroll sideways to read all columns.
| Situation | Approach to consider | Delivery check |
|---|---|---|
| Copy an approved record between systems | A conventional integration with fixed field mappings. | Check duplicates, retries, missing fields, and failed updates. |
| Interpret varied incoming documents | AI extraction followed by validation and review. | Test different formats, missing information, and incorrect values. |
| Gather evidence from several approved tools | An agent with a limited tool list and stopping rules. | Check tool permissions, sources, cost, and incomplete work. |
| Make a consequential change | A prepared action with a human approval step where required. | Confirm who approved it, what changed, and the recovery path. |
Match rules to predictable steps.
Calculations, scheduled exports, and routing with clear conditions usually suit conventional software. Describe the rules and test known inputs and results. Those rules can also check fields, enforce access, and move approved results within an AI workflow.
Identify where interpretation adds value.
An agent can interpret varied requests, compare documents, or choose an approved tool. Define the decisions it may make and the information it may use. Preparing an answer from policy documents and changing a customer’s account require different permissions.
Map the handoffs between people and software.
Map how work moves between AI, software, and people. Give each step a clear input, output, owner, and failure condition. Use additional agents when separate responsibilities or independent review improve the result enough to justify the extra cost and coordination.
Control actions separately from generated text.
Check permissions and approval when a tool or application performs an action. Validate inputs and record important changes with enough context for review. A model’s explanation cannot establish that an action was authorized or completed correctly.
Compare approaches using your cases.
Try fixed rules, agents, or a combination on the same examples. Include unclear requests, missing records, and tool failures. Compare useful results, review effort, and total operating cost. Active K Digital can help design both the workflow and the comparison.
Your starting checklist.
- Separate fixed rules from decisions requiring interpretation.
- Define each step's inputs, outputs and owner.
- Enforce permissions at the tool boundary.
- Specify approval, exception and recovery paths.
- Compare quality, review effort and total operating cost.