The problem was never defined precisely
Teams often begin with a model capability instead of a business decision or workflow. Without a clear user, input, outcome, and failure definition, a prototype cannot be evaluated meaningfully.
The system cannot access trustworthy context
AI quality depends on the information available at the moment of use. Missing permissions, stale documents, duplicated records, and unclear ownership quickly undermine confidence.
Evaluation and adoption arrive too late
Quality criteria, review workflows, monitoring, and user feedback should be part of the architecture from the beginning.
- Define representative test cases
- Measure both accuracy and workflow usefulness
- Design visible escalation paths
- Train users on capabilities and limits