AI risk guidance puts KM inside supervision and training

Filevine’s AI-risk analysis lists hallucinations, confidentiality, professional responsibility, bias, IP uncertainty and over-reliance as core risk categories. For KM leaders, the takeaway is that AI enablement cannot stop at a tool rollout; it needs approved sources, verification habits, supervision rules and training paths that turn knowledge practice into risk control.