Why Most Enterprise AI Fails After The Pilot Phase
Not a model problem. 73% of enterprise AI projects fail because organizations aren't ready—here's why.
Why it matters
Enterprise AI failures are primarily organizational readiness issues, not technology limitations. This challenges the narrative that better models solve adoption problems and highlights the critical gap between capability and deployment.
The key facts
7 to knowAI does not usually fail in production
Failure root cause: organizational readiness, not technology
Published by Forbes Tech Council (opinion/research piece)
Focuses on enterprise deployment patterns and governance
Most enterprise AI fails after pilot phase, not in production
Root cause: organizational readiness, not technical capability
Shift in thinking: from 'which model to deploy' to 'is the org ready to deploy'
Go to the source
Forbes Innovationforbes.com
Publisher excerpt: AI does not usually fail in production. More often, the organization is not ready for it.