Use AI where judgment and controls still matter
AI can support classification, extraction, summarization, and routing, but production workflows still need validation, privacy controls, exception handling, and human review where the cost of error is high.
Document processing
Combine extraction with confidence thresholds and review queues.
Human-in-the-loop
Define where review is required and how decisions are recorded.
Governance & evaluation
Test representative examples, protect data, and monitor failures over time.
A responsible implementation checklist
- Define the task, acceptable error rate, and fallback route.
- Use only approved data sources and services.
- Evaluate accuracy on realistic test data before release.
- Keep a human accountable for consequential decisions.
- Monitor drift, exceptions, and user feedback after launch.