Key Takeaway
The ideal AI pilot is not the highest-impact use case but the one with the best combination of clear success criteria, available data, manageable scope, and visible business sponsor.
Why Pilot Selection Matters
The first AI pilot can make or break an organization's AI journey. Choose too ambitiously and it stalls, eroding confidence and making future investment harder to justify. Choose too conservatively and it fails to demonstrate meaningful value, leaving stakeholders unconvinced that AI is worth pursuing. The pilot selection decision deserves more rigorous analysis than it typically receives, because its primary output is not the AI feature itself but organizational confidence in AI as a capability.
Step 1: Candidate Generation
Generate a broad list of candidate use cases from three sources: structured brainstorming workshops with each business unit (use the prompt 'where do humans do repetitive cognitive work that could be augmented by AI?'), review of the existing product backlog for features that were deferred because they required ML, and analysis of competitor products for AI features that your product lacks. Aim for 15-30 candidates before filtering. Do not evaluate feasibility at this stage; the goal is breadth.
Step 2: Feasibility Screening
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