Definition
AI waste
AI waste is the gap between what an organization spends or risks on AI and the value it can prove. It includes duplicate tools, unused seats, pilots that never ship, unsafe shadow use, outputs that need rework, and workflows where adoption rises while business results stay flat.
Last updated: 25 June 2026
Why it matters
Naming waste makes reduction legitimate: some AI should be stopped or consolidated, not celebrated.
Signals to watch
- Renewals continue without review
- Pilots never reach production
- Usage rises without value