1. Identify a task that repeats often
Observe actual work: who copies information, searches for a document or checks a deadline? Record frequency, time spent and errors. If the task changes with every case, clarify the method before automating uncertainty.
2. Choose between rules and AI assistance
Sending a form to a CRM or creating a reminder can follow defined rules. Interpreting a message or preparing a summary may justify AI assistance with checking. A chatbot is only one possible interface: an action inside your existing tools may address the need better.
3. Define exceptions before launch
What happens if a contact already exists, a document is missing or a customer has replied? Assign someone to take over each exception. Decide which actions may run and which need approval, especially before a message or an important change.
4. Test a limited scope
Prepare representative cases: a complete record, a duplicate, missing information, insufficient permissions and an unavailable tool. Check results, alerts and manual recovery. Expand when the team can recognise an error and take over.
| Task | Information required | What to watch |
|---|---|---|
| Prepare a follow-up | Contact, status, due date and latest exchange | Avoid chasing a case already resolved |
| Transfer a request to the CRM | Form fields and record creation rules | Avoid duplicates and flag missing fields |
| Search procedures | Current documents and viewing permissions | Refer to sources and flag when no answer is available |
Example: a quotation request arrives
A form sends a request. The flow looks for the contact, prepares the record and creates a task for sales. It may then suggest a draft reply for approval before sending. Missing data prompts a check rather than invented information. This is an illustrative scenario, not a completed client project.
How can you tell whether automation is useful?
Compare similar cases before and after the test: processing time, corrections, duplicates and unanswered requests. Subtract checking and maintenance time from time saved, then assess recurring costs. Set criteria before the pilot; no numerical improvement can be guaranteed without observation.
What to gather before our discussion
- One priority task, its frequency and current owner.
- Tools involved and available access or data exchange options.
- Usable examples, preferably fictional or anonymised.
- Rules, exceptions and approvals to retain.
- An expected result the team can check.
Key takeaways
Start with a clearly defined recurring task, choose the appropriate mechanism and assess the result within a limited scope. AI’s role depends on the content to handle, not an obligation to add it everywhere.