Five Pressures That Break AI Programs After the Pilot
TechTarget, Tuesday, August 18th, 2026
Data foundations, not model capability, determine which AI pilots successfully scale to production.
Enterprise AI programs fail during production scaling because of fragmented data pipelines built during pilots. Only 23% of organizations have fully integrated data for AI, while 60% report increased complexity.
Success requires addressing five pressures: data readiness speed, inference cost, scalable controls, data trust and governance.
Leading organizations partner externally, keep data in place rather than moving it, and treat the path from raw content to production as a single engineered flow.