Oracle Puts Agent Reasoning Where the Data Lives

Oracle wants your database to run the agents. The pitch landed March 24 at Oracle AI World Tour London: embed agentic reasoning directly into Oracle AI Database 26ai, and let the data layer handle what external orchestration layers cannot — low-latency access, consistent governance, and the long tail of enterprise data that makes production agent deployments fall over. Whether that architecture holds up in the real world is where the story lives.

The argument Oracle is making is coherent. Enterprise agent deployments have a predictable failure mode: they break at the data layer, not the model layer. "The struggle is running them in production," Matt Kimball, an analyst at Moor Insights & Strategy, told VentureBeat. "The gap is seen almost immediately at the data layer — access, governance, latency, and consistency." Oracle's counter-proposal is to co-locate the agent reasoning engine with the data itself, so the agent doesn't have to cross a network boundary to get what it needs. Steve Miranda, Oracle's vice president of applications development, described the design intent in an interview with Futurum: these agents are "designed to sit on top of existing applications to enable users to more efficiently handle work processes that traditionally would have required API calls." The data lives there; the agent should too.

Oracle calls this the Autonomous AI Vector Database, and it sits inside Oracle AI Database 26ai. The product is architecturally the convergence of Oracle's converged database strategy — one engine handling relational, vector, JSON, and graph workloads — with a layer of pre-built agents that reason over that data. The Private Agent Factory ships with three: a Database Knowledge Agent, a Structured Data Analysis Agent, and a Deep Data Research Agent, according to InfoWorld, each designed to operate on data inside the Oracle ecosystem without routing queries out to an external model provider. For Oracle shops, this removes a dependency. For everyone else, it's a platform lock-in bet dressed as a feature.

The feature set is real. Oracle AI Database 26ai on-premises became available for Linux x64 on standard hardware at the end of January 2026 after several delays, and the agentic capabilities were formally announced March 24 at Oracle AI World Tour London. Oracle said it has 63,000-plus certified experts trained in Oracle AI Agent Studio, according to Oracle's announcement — a number that signals where the revenue play is, not where adoption is. The named customers using agentic capabilities — Munich Re HealthTech, Rappi, Retraced, and Uniti — are early-stage deployments, according to Oracle's own blog, not proof points at scale. Oracle's claim that 97 percent of Fortune Global 100 companies trust it for their business data is a different product claim entirely; it's about existing database contracts, not agent deployments.

The skepticism from analysts is substantive. Balaji Abbabatulla, an analyst at Gartner, was direct in The Register's coverage: "Our position is that this sounds good but be cautious. It does not necessarily look as glittery as it sounds. There are challenges under the hood which are not being overcome right now." The specific challenge Abbabatulla flagged is data synchronization — Oracle cannot automatically sync different data repositories in the background without human expert configuration. Mickey North Rizza at IDC offered a more favorable read, calling it a significant shift toward "Agents as Apps" — the idea that agents become the new interface layer on top of existing enterprise software.

The architectural limit Oracle hasn't resolved is the same one it quietly acknowledges. Enterprises run on a patchwork of Oracle and non-Oracle systems, and the agent's world only works cleanly inside the Oracle perimeter. Maria Colgan, a distinguished product manager at Oracle, put it directly in VentureBeat's reporting: the company's own marketing materials admit "we know that that is not true" — referring to the assumption that all enterprise data lives in Oracle. Steven Dickens at HyperFRAME Research gave the sharpest frame: Oracle's move to label the database itself as an AI Database is "primarily a rebranding of its converged database strategy to match the current hype cycle." That's a fair read. The underlying technology is not new; what Oracle has done is wrap it in agentic framing and pre-built agent personas.

The demand signal is real. A Futurum survey found 39 percent of organizations expect GenAI to be delivered primarily via agents, with 43 percent ranking it as a top software purchase criterion. Futurum projects the broader data and AI market will reach $541.1 billion in 2026, growing at 16.9 percent CAGR to surpass $1.2 trillion by 2031. Oracle is arguing it has the data infrastructure to win that market. Whether it does depends on what you think the unit of enterprise AI competition actually is.

Juan Loaiza, Oracle's executive vice president of database technologies, put the stake in the ground: "The next wave of enterprise AI will be defined by customers' ability to use AI in business-critical production systems." That's correct. The question is whether the data synchronization problem — which Gartner calls a blocking issue, which Maria Colgan calls the real world, and which Oracle's own documentation quietly sidesteps — gets solved before enterprises decide the better move is to fix their data infrastructure first and pick their agent framework second.

The dependency graph nobody in the announcement wants to show you is the one where the agent is only as good as the data it can reach — and Oracle still cannot reach all of it.