The key takeaways
- Start with a bounded process and a measurable outcome.
- Prepare information, permissions and human review.
- Evaluate operating effort before scaling.
Choose a process with a clear purpose
Define the task before selecting the tool. Consider who performs it, how much effort it takes and where errors or rework occur. A suitable first use case has a clear user, a bounded information source and an outcome you can assess. Avoid starting with a broad instruction to introduce AI everywhere without identifying a problem.
Prepare the information it will use
Review where the relevant information lives, whether it is current and who is allowed to access it. An assistant should not make poorly governed documents easier to discover. Identify a content owner and a way to update or withdraw information. Consider whether confidential material is suitable for the proposed platform and its contractual terms.
Decide where human review belongs
Not every output should trigger an action. Establish which responses are advisory, which require validation and which decisions remain with an authorised person. An assistant that drafts a response needs a different control model from an agent that changes a record or sends an external message. Make those boundaries clear to both designers and users.
Evaluate more than a happy-path demo
Create representative questions and include incomplete, ambiguous and out-of-scope requests. Check whether the system identifies useful sources, admits uncertainty and handles information it should not disclose. NIST’s AI risk resources provide a structured way to consider risks. Your own acceptance criteria should reflect the process and the consequences of an incorrect result.
Count the operating work
Consider licences, integration maintenance, usage, content updates, support and the effort needed to review outputs. A prototype can seem inexpensive while relying on manual work that was never measured. Assign an owner for service changes and failures, and establish a route for users to report unhelpful or incorrect results.
Measure before expanding
Record a baseline and compare the pilot against agreed measures such as handling time, useful responses, review effort or rework. Include feedback from the people who use the process. Expand only after reviewing usefulness, risks and operating cost. Some pilots will justify a wider rollout; others will reveal that a simpler workflow or a better knowledge base should come first.
Further reading
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