AI RESOURCE CONTROL · AI GOVERNANCE PROTOTYPE
What happens when AI demand exceeds capacity?
As teams rely more on AI, not every request should receive the same level of compute, budget or human review. Organizations may need ways to route work by priority, risk and value without turning every constraint into a denial.
This concept explores a control surface for reviewing flagged AI requests, recommending lighter alternatives or scheduled processing, and preserving premium capacity for work that needs it most.
Scenario
You’re reviewing AI usage across internal teams. Sales Operations is nearing its weekly allocation, and several requests need a routing decision before they use premium capacity.
Open the queue to review each request, compare the recommended route, and choose whether to approve, simplify, defer, or send it back for a narrower scope.