81% of Enterprises Stall AI Projects Due to Data Governance Gaps…

Event summary

81% of enterprises delayed, scaled back, or abandoned AI initiatives in the past 12 months due to data permission and governance issues.
AI-driven marketing and segmentation initiatives stalled most often (41%), followed by data monetization (38%) and personalization (30%).
Only 23% of engineering hours in AI initiatives go toward feature development; 77% are spent on data infrastructure repair and governance workarounds.
Only 15% of enterprises have all four foundational AI governance capabilities fully in place.
Transcend introduces Encoded AI Governance framework to address the infrastructure gap.

The big picture

The report highlights a structural mismatch between AI ambitions and data infrastructure, with legacy systems failing to enforce permissions in real-time. As AI initiatives proliferate, the gap between policy and enforcement is becoming the primary barrier to revenue growth. Boston Consulting Group projects $2 trillion in revenue shifting to personalization leaders over the next five years, making data governance a critical competitive differentiator.

What we're watching

Governance Dynamics: How enterprises will adapt their data governance frameworks to support AI initiatives at scale.
Execution Risk: Whether companies can effectively implement Encoded AI Governance to unblock stalled AI projects.
Market Differentiation: The pace at which leading enterprises will pull ahead by resolving data permission and governance gaps.