The fastest way to waste an AI budget is to start from the technology — “where can we use AI?” It shows up in the numbers: the share of companies abandoning most of their AI initiatives jumped to 42% in 2025, up from 17% the year before, and the average organization scrapped 46% of its AI proof-of-concepts before they reached production, according to S&P Global Market Intelligence data reported by CIO Dive. The operator’s way is to start from the bottleneck: where is the business actually constrained, and what would it be worth to relieve it?
The framework
- Find the bottleneck. Where does work pile up, margin leak, or a key person become a single point of failure?
- Size the prize. Put a dollar (or hours) figure on relieving it — annualized. (Size the prize with the Value at Stake calculator.)
- Score on three axes. Business impact, execution complexity, and speed to value. (The AI Use Case Canvas gives you one page to run this.)
- Pick the one with the best impact-to-effort ratio and a clear KPI.
Why bottlenecks beat tech-stack tours
- The value is already quantified — it’s the cost of the constraint
- It’s specific, so the build has a clear target and a baseline
- Relieving one bottleneck usually exposes the next, giving you a roadmap
Pick the number you want to move, and the build picks itself. Scope it as a Value Sprint, or run the prioritization inside AI Office.