Why AI PoCs Fail (And How to Avoid It)

Many AI PoCs fail for boring reasons: unclear goals, poor data, or lack of stakeholder alignment. Understanding these patterns helps you design PoCs that actually lead to decisions.

• Problem definition is vague or keeps changing.
• Data is missing, low quality, or not representative.
• Stakeholders never agreed on success metrics.
• The team discovers key technical or business blockers too late.

The AI PoC Development pillar page describes how to structure PoCs to reduce these risks.