Managing the Hidden Debt of AI-Generated Software

AI-assisted delivery can increase output while creating risks that conventional technical-debt metrics do not reveal. The article distinguishes unowned code debt—production code no engineer fully understands—from data drift debt, where live behavior diverges from original assumptions after deployment. It argues that velocity, coverage, and deployment frequency should be supplemented with measures of code provenance, review depth, ownership, maintainability, and drift. Technology leaders should audit high-impact modules before unexplained code or changing data becomes an operational, security, or compliance incident.