Separate interpretation from execution
A purchase request may arrive as a structured form or a loosely written email. Checking a mandatory field is a rule. Interpreting what the email is asking for may benefit from AI. Posting an approved transaction should follow explicit business controls. These are different responsibilities inside the same process.
This illustrative example helps you avoid adding AI to a step that already works reliably with a simple rule.
Use workflows for known routes
A workflow fits steps with defined inputs and outcomes: checking completeness, applying an approval threshold, sending a reminder or updating a record after approval. Document what happens when the integration fails, when an approver is absent and when the request is cancelled.
Predictability still requires good design. Retries can create duplicate records unless an operation recognises that it has already completed.
Use agents where context changes
An agent can help interpret natural language, retrieve relevant information and select from approved tools. Suitable responsibilities might include identifying an enquiry’s intent or preparing a response from several approved documents.
Give the agent a narrow task and defined escalation criteria. More autonomy is not automatically a better design; the right level depends on the consequence of being wrong.
Combine them at an explicit handoff
A possible pattern is: receive a request, use AI to propose a category, validate the required fields, ask a person to approve consequential actions, and execute the authorised workflow. Microsoft Copilot Studio supports combining agents and workflows.
Pass structured data at the handoff and validate it. Record the request identifier, authorised action and outcome so the team can investigate a failure without reconstructing a conversation.
Make the choice with a process map
For each step, ask whether the input is structured, whether the route is known and whether a mistake is reversible. Identify the decision owner and acceptable failure behaviour. Compare a workflow-only option with an AI-assisted option before introducing complexity.
Start by automating the predictable part. Add AI where it resolves a specific limitation, then test the complete process rather than the model response alone.
Further reading
Official documentation supporting the technology references. The implementation recommendations and scenarios are sbPowerDev’s editorial guidance.
