Enterprise organizations struggle to justify AI investments as sprawl, rising GPU costs, and lack of visibility transform AI from a technical challenge into a board-level financial problem.

Enterprise AI is shifting from a 'what can we build' phase to a 'how do we measure ROI' phase, with organizations facing AI sprawl and skyrocketing inference costs

Brian Gracely at Red Hat highlights the operational reality: companies deploying tens of thousands of AI licenses like Copilot lack visibility into actual business value while paying premium GPU computing costs

The 'Day 2' moment of moving from pilots to production reveals that governance, cost control, and sustainability are harder challenges than building the initial AI systems

Cost management for enterprise AI investments has become a board-level concern as organizations seek to control spending on expensive GPU infrastructure