Separate the decisions inside the task
The useful starting question is what the software needs to decide. A workflow that copies an approved record into another system has a different problem from one that must understand an open-ended customer request. Both may benefit from automation, but they need different forms of control.
Break the task into receiving information, interpreting it, choosing a next step and carrying out that step. Some stages may follow explicit rules while others require interpretation. This prevents a broad label such as “AI customer service” from hiding the actual decisions, dependencies and permissions inside the work.
Match the approach to the decision
| Approach | Suitable task | Main question to resolve |
|---|---|---|
| Rule-based automation | Carry out a defined action when known conditions are met. | Are the conditions, exceptions and expected results explicit? |
| AI-assisted step | Interpret a message, summarize material or prepare a draft within a defined workflow. | How will the interpretation be checked before anyone relies on it? |
| AI agent | Choose among permitted steps or tools to pursue a bounded task. | Which actions may it take, and when must it stop or involve a person? |
Keep known business rules explicit
If the business can state the decision precisely, start by expressing it as a rule. For example, a customer’s choice of topic can determine which team receives a request. There is little reason to ask a model to infer a choice that the user has already supplied clearly.
Rules still need thoughtful design. Decide what happens when a field is missing, a destination system is unavailable or a request arrives twice. Document who owns unresolved items. Predictable decision logic does not remove operational complexity; it makes a defined part of that complexity easier to inspect and test.
Human handover is part of the product
Nexo’s WhatsApp platform combines conversational flows, business-system integration and routing to human agents, using Meta’s official Cloud API. The customer conversation and the point where a person takes over are both part of the product. Plan that transition alongside the automated steps, so the team can continue handling a request when it needs human attention.
For a new workflow, specify what the receiving person needs: the original request, the information already collected, any actions attempted and the reason for handover. Decide who owns the item while it waits. A handover button alone does not answer these questions or establish that the customer’s issue has been resolved.
Evaluate the difficult cases as well as the easy ones
Prepare examples before implementation. Include clear requests, ambiguous wording, missing information, contradictory records and requests outside the permitted scope. Define an acceptable outcome for each. Sometimes that outcome is an answer; sometimes it is a refusal to act, a clarification question or a handover.
Review interpretation and action separately. Did the system understand the request? Did it use information the user was allowed to access? Was the proposed action appropriate? Was the action actually completed? A fluent response answers none of those questions by itself. Track corrections and unresolved cases alongside completed tasks so an apparent success rate does not hide the work still falling to the team.
Define a first workflow you can assess
Choose a narrow task with an identifiable owner and a reviewable result. Expand only after you understand how it behaves on ordinary work and on the exceptions that matter to your team.
- Which decisions can be written as fixed rules?
- Where does interpreting varied information add value?
- Which sources may the system read, and which actions may it take?
- What requires approval, clarification or human handover?
- Which examples will show that the workflow is useful and stays within its scope?
Start with one task worth improving.
Describe the request, the information it depends on and the point where your team needs help.
Discuss an automation workflow
