Begin with the decision or task
Useful AI projects start with a repeated task, a difficult decision or an information bottleneck. Starting with a model and searching for a use case usually produces novelty rather than durable value.
Define who uses the output, what they need to decide and what acceptable quality looks like before selecting the technology.
Keep accountability visible
AI-generated recommendations should be presented as support, not certainty. Users need enough context to review the result, correct assumptions and understand the next step.
Sensitive inputs, retention and provider policies must be considered before information is sent to an external model.
Measure the whole workflow
A faster generation step does not automatically create a faster process. Measure review effort, error handling, handoffs and downstream work as well.
The best opportunities usually combine a capable model with clear data, deliberate constraints and a workflow that keeps human judgement where it matters.