Choose a bounded task
“Add AI to the system” does not define an operational problem. Choose a specific activity such as summarising accessible text, suggesting a category or helping users find information. Its inputs, outputs and users need to be clear so quality can be evaluated against real examples and further development can be justified.
Design data access with the use case
An assistant should not gain access to all information simply because it connects to a system. Review data scope, the user’s permissions and the processing destination. Source quality matters too: fluent wording is not evidence of correctness. Where appropriate, the user experience should include a route to the source and a clear expression of response limitations.
Distinguish suggestions from actions
Summarising a request differs from changing a contract’s state or sending a message on an organisation’s behalf. As the impact increases, controls, confirmation and reviewable history become more important. Decision ownership must remain clear, with an opportunity to understand and approve consequential actions. Generated output should not automatically become an irreversible operational result.
Make evaluation part of the product
Prepare cases covering ordinary, ambiguous and out-of-scope requests. Examine incorrect answers, inability to answer and cost per task alongside any time saved. A limited, measurable starting point makes improvement possible. Useful intelligence emerges when the tool’s behaviour matches the real responsibilities of the workflow.