Too Many AI Use Cases, Too Little Impact
Organizations have 50+ AI pilots. Most deliver nothing. Here's how to pick the ones that matter.
Why it matters
AI deployment has shifted from 'can we build it?' to 'should we build it?' — practitioners now face a prioritization and ROI measurement problem that separates real value from pilot theater. This is a business strategy story, not a technical one.
The key facts
8 to knowProblem framed as prioritization, not capability
Focus on business value, impact, feasibility, and strategic alignment
Organizations struggling to translate pilots into measurable outcomes
Forrester advisory/best-practice content
Problem framed as prioritization, not AI capability gap
Evaluation criteria: business value, impact, feasibility, strategic alignment
Widespread pilot-to-production bottleneck in organizations
Focus on measurable business outcomes vs. proof-of-concept proliferation
Go to the source
Forrester Blogforrester.com
Publisher excerpt: Organizations are flooded with AI ideas, pilots, and proofs of concept, yet many struggle to translate them into measurable business outcomes. The problem is not a lack of AI use cases. The problem is prioritization. Learn how to evaluate AI opportunities through the lens of business value, impact,…