Memory is the moat: MongoDB’s Ashish Kumar on why governance, not model choice, will decide who gets AI agents into production
Somewhere in your enterprise, an AI agent is about to call a sub-agent, which will call another sub-agent, which will call a tool, which will reach into a system of record. Now ask a simple question: on whose authority did that chain run, and can you prove it?
For most CIOs today, the honest answer is no. That gap, more than model quality or GPU budgets, is what keeps agentic AI stuck in proof-of-concept purgatory. Gartner has predicted that more than 40 percent of agentic AI projects will be cancelled by the end of 2027, citing escalating costs, unclear business value and inadequate risk controls.
MongoDB’s SVP Ashish Kumar thinks he knows how to close that gap, and he has a rare vantage point from which to say so. Before joining MongoDB roughly three years ago, when it acquired the startup he ran, Kumar spent years at Google, most recently...
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