Scaling agentic AI means trusting your data - here's what most CDOs are investing in
Agentic AI adoption surges, but 50% of companies cite data quality as their top deployment barrier.
A major survey of 600 Chief Data Officers reveals that while agentic AI adoption is accelerating—reaching 47% of companies, with 31% more planning adoption in the next year—significant roadblocks remain. The report, conducted by Informatica, Wakefield Research, and Deloitte, found that half of all agentic AI adopters cite data quality and retrieval issues as their primary deployment barrier, with 57% viewing data reliability as the key obstacle to moving AI projects from pilot to production. This comes as overall generative AI adoption in large companies ($500M+ revenue) has jumped to 69%, up from 48% just a year ago, highlighting a rapid but fragile expansion.
To address these foundational challenges, data leaders are making substantial strategic shifts. A striking 86% of CDOs report they will increase investments in data management over the next two years, focusing on data privacy/security (43%), AI governance (41%), and workforce upskilling (39%). The urgency stems from a governance gap: 76% of leaders admit their visibility and governance have not kept pace with employee AI use. The path forward is clear—scaling agentic AI, which promises benefits like enhanced customer experience and improved decision-making, is fundamentally dependent on building trustworthy, well-managed data foundations before agents can operate reliably at scale.
- 47% of companies have adopted agentic AI, with adoption in large firms ($500M+ revenue) reaching 54%.
- 50% of agentic AI adopters cite data quality and access as their top barrier to deployment and scaling.
- 86% of Chief Data Officers plan to increase data management investments in 2026-2027, with 43% focusing on privacy/security.
Why It Matters
Massive new data infrastructure investment is required to turn promising AI agent pilots into reliable, scalable business operations.