AI Due Diligence Checklist 2026: How To Avoid AI Implementation Failures, Security Risks, And Cost Overruns
Security Boulevard, Wednesday, April 1st, 2026
AI has moved from experimentation to core business systems. In first quarter of 2026, we saw companies push AI into production faster than ever. Copilots shipped in weeks. Internal tools were replaced with AI-driven workflows. Vendors promised quick wins.
And then the issues started showing up.
Systems that worked perfectly in demos began failing in production. Outputs were inconsistent across similar inputs. Teams could not explain why the model behaved differently day to day. In some cases, AI features had to be rolled back after users lost trust in the results.
Cost was another shock. What looked manageable in a pilot quickly became unpredictable at scale. Token usage spiked. API dependencies grew. Finance teams started asking questions engineering could not answer clearly.