CIO AI
2026-08-13 02:07 UTC
Score 55.0
USR-0125-20260813-global-ai-ne-28beffcd
Full article
Enterprises have built their data systems for humans, but AI agents need a whole new infrastructure. Separate research from Cloudera and Google/MIT found that, not surprisingly, there is fervent enterprise interest in AI agents, but underlying infrastructure struggles to keep up. Deployments continue to be hampered, sometimes even abandoned, largely due to issues with data access, context, and governance. “Enterprise adoption of agentic AI is on the cusp of an extraordinary acceleration,” the Google/MIT report noted . “As organizations look to scale agentic AI across the enterprise, they cannot ignore their data systems.” Resolving data bottlenecks, then, should be an immediate priority. Projects delayed, inaccessible data Cloudera’s report , created in partnership with Wakefield Research, describes the need for a “great AI re-architecture.” Of the 1,500 enterprise architects and cloud infrastructure leads surveyed, a stunning 95% said they had delayed or cancelled AI projects, in some cases six or more, in the past year, due to issues with data governance, compliance, or regulatory issues. A wide majority also reported that AI integrations have changed their data storage and architecture practices, AI workloads have increased infrastructure costs, and current data architecture requires a “significant overhaul” to meet AI goals. “Even if enterprises are ready to use AI, many are coming to the realization that the foundational infrastructure it relies on is not,” the report n…
