Start with a bounded task
Choose a repeatable activity with a clear input and a reviewable output: grouping customer questions, drafting variations of approved copy or summarising a campaign report. Broad instructions to “run all marketing” hide too many decisions.
Document what success looks like. For a draft, that might mean factual accuracy, brand tone and usefulness. For a workflow, it includes correct routing, error handling and whether the person receiving it has enough context.
Give the model a reliable source of truth
Maintain approved business facts, product details, terminology and examples. Keep confidential information out of tools unless the data handling has been reviewed and authorised. Model providers have different retention and training settings.
Ground outputs in those sources and require uncertainty to be visible. A polished answer is not evidence that the answer is correct. Review citations and claims against the underlying material.
Make review proportional to the decision
A private brainstorming list can have a lighter review than a published health claim or a message to a customer. Define which actions require a person and which routine steps can proceed under an agreed rule.
Maintain a way to pause the workflow. Log enough to diagnose a failure without copying unnecessary personal data into every tool. Test unusual inputs and provider outages before expanding the scope.
Measure usefulness, including the review time
Compare the total effort before and after: setup, output review, corrections and maintenance. Faster drafting is useful only if the final material remains accurate and relevant.
Scale the tasks that consistently pass review. Keep model/API costs, platform permissions and the human handoff visible in the operating plan. AI is most useful when it improves a defined part of the business.
Turn the idea into a practical next step.
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