What this article covers
A useful pilot starts with a bounded task and an approval criterion. Summarizing an alert is different from authorizing a tool to block an account. Evaluation must consider both response quality and the consequences of a wrong decision.
1. Choose a task and a baseline
Consider drafting an incident summary from records that have already been reviewed. Define who reads the result, which fields are required and which decisions remain with the analyst. Set aside representative cases, including incomplete alerts and false positives, to compare the current workflow with the pilot.
A successful demonstration is not evidence of performance across all incidents. Record the model version, instructions and evaluation set so that you can repeat the comparison.
2. Set boundaries for data and permissions
Map what leaves the environment: records may contain names, IP addresses, identifiers or secrets. Remove unnecessary information and check vendor retention, administrative access and data use. Local deployment also requires access controls and protected logs.
- Use synthetic or appropriately prepared data in the initial evaluation.
- Keep test accounts separate from production credentials.
- Restrict connectors to read access and essential resources.
3. Test failures before allowing actions
The NIST AI 600-1 profile describes risks specific to or amplified by generative AI, including confabulation and information security. Include an alert containing malicious instructions, a contradictory source and a question with insufficient supporting evidence in the pilot.
The expected response may be to withhold a conclusion or request review. The model must not turn text inside a record into authorization to run commands, open links or transmit data.
4. Measure quality and review effort
Count unsupported conclusions, incorrect fields and cases requiring rework. Measure total time, including analyst verification, and compare similar cases. Decide in advance which errors rule out use; a good average cannot compensate for exposing a secret.
For automated actions, require authorization outside the model, minimal scope, an audit trail and a tested way to stop the workflow.
5. Decide using evidence from your environment
The pilot deliverable should include scope, sample, results, limitations and a decision owner. Expand one use case at a time and reassess changes to models, data or connectors. An AI tool can support the work; it does not, by itself, establish that an operation is secure.
Use the AI checklist to structure the evaluation and explore the approach presented by Cortex.