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.

Full report : Separate studies conducted by Google/MIT and Cloudera both point to the same problem: Agents can’t reliably act on data they can’t access, understand, or retrieve in real time.