Why Most Organizations Fail at AI, and the Mental Model That Fixes It
MIT 2025 found that 95% of enterprise GenAI pilots return zero P&L impact. The cause is rarely the model. It is the question being asked. Most companies are calling chatbots agentic, supervising AI like a junior intern, and asking where AI fits instead of which problems would change shape if intelligence were unlimited and autonomous. Here is the reframe that fixes it.
Key takeaways
- MIT 2025 shows 95% of enterprise GenAI pilots deliver zero measurable ROI. The cause is rarely the model. It is the question being asked.
- Most 'agentic' deployments are chatbots in disguise. No agency, no autonomy, no goal pursuit. The label change does not change the architecture.
- The reflex to supervise AI 100% imposes a hidden tax that erodes the productivity gain it was meant to protect, and ignores that frontier models now solve problems humans could not.
- Asking 'where does AI fit?' guarantees mediocre returns. Asking 'which problems would change shape if intelligence were unlimited and autonomous?' reveals the real opportunity.
- The winning reframe is Intelligence as a Service: unlimited, autonomous, on-demand. Design workflows around delegation, not supervision.