Most enterprises have committed budget to AI, but few have built the data infrastructure needed to turn that spending into scalable AI outcomes.

The problem is less about model capability than it is about data discipline. As organizations race to deploy, many are discovering that without trusted, governed data at the foundation, scalable AI outcomes remain out of reach. That reckoning is upending how both technology platforms and systems integrators approach the enterprise AI journey, according to Sunil Varanasy (pictured, right), data and AI head for manufacturing, logistics, energy and utilities at Cognizant Technology Solutions Corp.

“We’re all trying to solve the AI problem, but we are not trying to understand, ‘Is my data good? Is the quality of the data good? Can I trust this data?'” Varanasy told theCUBE. “If I go back in any client meeting and ask them, ‘Do you have a proper stewardship established? Do you know who the data product owners are?’ — 50% of the room is silent. That’s the problem we’re trying to solve. AI to me is icing on the cake.”

Varanasy and Brian Hamel (left), chief revenue officer at Qlik Technologies Inc., spoke with theCUBE’s Rebecca Knight at Qlik Connect 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how trusted data, ecosystem partnership and rapid iteration drive repeatable outcomes across manufacturing, logistics and beyond. (* Disclosure below.)

Scalable AI outcomes start with data stewardship

Research from Qlik found that while 97% of enterprises have committed budget to agentic AI, far fewer have a defined return-on-investment framework. The disparity is less surprising than it seems — enterprise AI adoption is following the same uneven, stage-by-stage pattern that defined the early cloud era, according to Hamel.

“Every customer’s at a different stage. It reminds me of cloud 15, 20 years ago,” Hamel said. “When you think about the cloud journey, [we’re now] in an AI journey.”

A key part of that journey for Qlik relies on its partner ecosystem. Cognizant recently won Qlik’s Global System Integrator Innovation Partner of the Year Award and launched a data product as a service for asset and predictive maintenance — a sector where about 80% of clients still have not solved the core problem, Varanasy noted. The go-to-market collaboration has shifted from reactive to proactive, with the two companies aligning on solutions before bringing them to customers, and moving from one-off wins to repeatable outcomes through a compressed development cycle that takes manufacturing clients from prototype to production-ready in as little as six weeks.

“You understand, you adapt, you learn, and you improve,” Varanasy said. “As we are rolling out use cases, we are also looking at capabilities that are reusable components that can be leveraged for the broader organization.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Qlik Connect 2026:

(* Disclosure: TheCUBE is a paid media partner for Qlik Connect. Neither Qlik, the sponsor of theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE