In the Media

Imagine an AI agent tasked with preparing a customer account summary. To complete the job, it requests information from several business systems, including customer records, financial data and internal correspondence. Some of that information may be relevant. Some may be sensitive or entirely unnecessary. But if the AI decides it needs the information, who determines whether it should actually receive it?

​For years, the semantic layer was the behind-the-scenes part of the data stack. It sat beneath dashboards, making sure “revenue” meant the same thing in finance as in sales. When it was missing, a human analyst usually noticed and filled the gap. Agentic AI has removed that safety net. Standards such as the Model Context Protocol (MCP) have made it remarkably easy to connect AI agents to enterprise data systems.

U.S. enterprises are moving quickly beyond generative AI experimentation toward systems capable of doing something fundamentally different: acting. AI agents can plan tasks, invoke tools, interact with applications and increasingly make decisions with limited human supervision. The potential gains in productivity and automation are enormous.

Kevin Bohan, Director of Product Marketing at Denodo, joined the Government Technology Insider podcast to unpack why governed access is essential as AI adoption grows.

A capable AI model is only part of the answer. To be useful in day-to-day operations, AI needs reliable information and a clear, responsible way to act on it. That can be difficult when important data is spread across many systems and decisions need to involve business rules, employees, or approvals. The partnership between Camunda and Denodo brings these needs together.

Ravi Shankar, Senior Vice President and Chief Marketing Officer, Denodo, explains why, as AI agents take on bigger roles across the Gulf, trust will depend less on the models and more on the quality and governance of the data behind them.

Denodo has published research by Veqtor8 on the financial impact of its AI data layer for enterprise agentic AI. The study found a 290% return on investment over three years.

Denodo, the AI data layer company, announced the findings of a comprehensive independent study conducted by research firm Veqtor8. The research report, titled “The ROI of an AI Data Layer for Agentic AI,” reveals that enterprise deployment of a governed AI Data Layer delivers a 290% return on investment (ROI) over three years, enables 3x faster agent deployment velocity, and achieves a 68% reduction in AI operating costs.

Denodo announced findings from a comprehensive independent study by research firm Veqtor8. The research report, titled “The ROI of an AI Data Layer for Agentic AI,” reveals that enterprise deployment of a governed AI Data Layer delivers a 290% return on investment (ROI) over three years, enables 3x faster agent deployment velocity, and achieves a 68% reduction in AI operating costs.

Denodo has announced findings from an independent study by research firm Veqtor8, which reports that deploying a governed AI data layer can deliver a 290% return on investment (ROI) over three years, accelerate AI agent deployment threefold and reduce AI operating costs by 68%.