Good candidates have repetition and reviewable outputs
Summarising calls, classifying enquiries, drafting reports and searching an internal knowledge base can reduce repetitive work. The output can be checked before it reaches a customer or changes a record.
Start with a measurable queue rather than a broad “AI transformation”.
Risk changes the architecture
A confident model can still be wrong. Financial, legal, medical, employment or contractual outputs need stronger controls and often should remain advisory only.
Use source references, permissions, approval steps and audit logs where consequences matter.
Data access is a design decision
Limit each workflow to the information it needs. Understand where prompts, documents and outputs are processed and retained.
Do not place sensitive customer data into an unapproved tool because the interface is convenient.
Prove value in a pilot
Measure time saved, error rate, adoption and exception volume. Compare against the real baseline, including review time.
Scale only when the workflow is reliable and the team knows how to intervene.
How this becomes a project
A useful next step is a short audit of your current pages, search footprint, proof and measurement. The output should identify the few constraints worth fixing before more content or media is added.