AI as the Permanent Intern: The Role-Task Gap in Enterprise Workflows
· 9 min read
There's a pattern that appears in nearly every enterprise AI deployment: the tool performs brilliantly in the demo, ships to production, and then quietly stalls at 70–80% of its potential. Teams attribute the stall to model quality, context window limits, or retrieval failures. Most of the time, that diagnosis is wrong. The actual problem is that they're asking the AI to play a role it structurally cannot occupy — not yet, possibly not ever in its current form.
The gap between "AI can do this task" and "AI can play this role" is the most expensive misunderstanding in enterprise AI.
