![Andrew Milroy ](/sites/default/files/author-portraits/Andrew%20Milroy.jpg)



 

##### Andrew Milroy 

Chief Analyst

 ![](/sites/default/files/vector8.png)



 

 

 ![Dominic Sartorio](/sites/default/files/author-portraits/headshot-DominicSartorio.jpg "VP of Product Marketing, Denodo")



 

##### Dominic Sartorio

VP of Product Marketing

 ![](/sites/default/files/logo-denodo-new.png)



 

 

 

 

**Most enterprises can build a few AI agents. The economics change when they try to scale to hundreds**. In this 30-minute analyst briefing, Andrew Milroy, Chief Analyst at Veqtor8, talks with Dominic Sartorio, Head of Product Marketing at Denodo, about the ROI of using an AI Data Layer for agentic AI. Andrew conducted an independent analysis of customers' enterprise-wide AI deployments and authored the study, showing a 290% average three-year ROI, and detailing how this is achieved.

Andrew explains that **scaling and reuse** are the key challenges an [AI Data Layer](https://www.denodo.com/en/data-management/ai-data-layer) solves; why **integration followed by token consumption are the biggest cost drivers**; and how the **three common architectural patterns that enterprises run today** (custom integration, lakehouses and hyperscaler ecosystems) **hold up as agents multiply.** He also shares what didn’t make it into the report, from infrastructure costs many large organizations haven’t yet thought through to the early warning signs that **an architecture built for pilots won’t scale.**



 

 

 

  

 ![Scaling AI Agents: Where an AI Data Layer Delivers ROI ](/sites/default/files/WP-ROIAIDataLayer-mockup-Details.png)   **Register for APAC** 

 Wednesday, November 18 - 10:30am IST | 1:00pm SGT | 3:00pm AEST  

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 Wednesday, November 18 - 11am CET | 10am GMT 

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 Wednesday, November 18 - 11am PST 

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