Choose a specific task
Consider work such as classifying incoming requests, preparing a first draft or finding relevant material in an approved knowledge base. Specify the input, expected output and person responsible. Avoid beginning with an instruction to automate an entire department before understanding its exceptions and decisions.
Assess the data and consequences
Check what information the tool receives, which permissions apply and how the provider handles it. Identify errors that would create meaningful customer or business harm. Restrict access appropriately and keep review requirements proportionate to the use case. Do not assume a convincing answer is accurate.
Measure the full workflow
Compare completion time, output quality, review time and operating cost against the current process. Include failed attempts and correction effort. Model usage costs and operational dependencies. A faster draft creates limited value if checking it takes longer than completing the original task.
Expand only after a controlled trial
Give the trial an owner, limited scope and review date. Keep a way to stop or revert the workflow. Record the model, instructions and evaluation method so changes can be assessed. NIST’s voluntary AI risk framework is a useful reference for considering risks across an AI system’s lifecycle.
Your next steps
- Choose one repeatable task.
- Establish time and quality baselines.
- Check data permissions and provider terms.
- Assign human review where needed.
- Measure errors, review time and total cost.