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Why Do Most AI Pilots Fail to Scale?
Enterprise AI pilots fail to scale primarily due to five organizational gaps—missing data infrastructure, absent change management, unbuilt governance, misaligned metrics, and evaporating executive sponsorship—rather than technology underperformance. The article draws on BCG and RAND research showing that 80% of AI projects fail to deliver business value, with only 5% of organizations qualifying as "future-built" and extracting AI value at scale.
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Summary
Enterprise AI pilots fail to scale primarily due to five organizational gaps—missing data infrastructure, absent change management, unbuilt governance, misaligned metrics, and evaporating executive sponsorship—rather than technology underperformance. The article draws on BCG and RAND research showing that 80% of AI projects fail to deliver business value, with only 5% of organizations qualifying as "future-built" and extracting AI value at scale.
Tags
ai-adoption · enterprise-ai · pilot-scaling · change-management · data-infrastructure · ai-governance · digital-transformation
Key entities
Jill Davis (person, 0.95) · BCG (organization, 0.97) · RAND Corporation (organization, 0.95) · Gartner (organization, 0.97) · AI pilot scaling (concept, 0.98) · AI maturity model (concept, 0.88) · change management (concept, 0.85) · data infrastructure (concept, 0.87) · BCG Build for the Future 2025 study (event, 0.9)
Classification
analysis · language en · status final
Provenance
claude-opus-4-6 via @stacklist/mcp-server@2.0.0, confidence 0.85, 8 Jun 2026