Enterprise AI: Join With Your Whole Team or Don't Join

Why Individual AI Champions Fail at Scale

This short enterprise case study captures one crucial insight about AI adoption that's easy to miss: the "hero problem."

"Only allowed to join if they joined with the whole team." When they announced the ChatGPT Enterprise pilot, they had 2x more requests than seats. But instead of distributing licenses to individuals, they required team-wide participation. The reasoning: "It's not dependent on one smart guy building a GPT for his team and then moving on and no one understood what he did. Rather we wanted to get it into the team DNA."

Decentralized decision-making helps AI adoption. Organizations that push decisions "very much lower in the organization" are seeing advantages: "that's a strength right now when we work with OpenAI with ChatGPT - it allows the organization to experiment, to test, and there's also a lot of pull in the organization to really get it."

"The pace of requests is just expanding." They're experiencing acceleration in both adoption speed and results quality. "You expect results but it's going faster. It's going faster in time. It's going faster in quality."

6 Insights on Enterprise ChatGPT Adoption

• Team-wide adoption required - No individual licenses; prevents hero/bus-factor problem
• 2x oversubscription - More demand than seats at pilot announcement
• "Team DNA" - Goal is collective capability, not individual expertise
• Decentralized decisions - Push AI experimentation authority down the org
• Pull vs push - Strong organic demand from the organization
• Accelerating pace - Request rate expanding; results faster than expected

What This Means for Enterprise AI Strategy

The "hero problem" kills AI adoption - one smart person builds something, then leaves, and nobody understands what they did. The fix: only allow team-wide participation. AI capability needs to be in the team DNA, not dependent on individual expertise.