‘Nobody wants to be a news story,’ but bad data is making that a real risk factor for enterprise AI

Data quality is emerging as the critical gating factor separating enterprise AI projects that produce results from those that fizzle out.

However, leadership pressure to move fast on AI is running into a difficult reality at many organizations, according to Matt Hayes (pictured), general manager of the data business unit at Qlik Technologies Inc. Companies that have spent years labeling, integrating and governing their data are learning that “AI-ready” is a much higher bar than “analytics-ready.” When agents start making autonomous decisions, those gaps don’t just surface — they can cause real, public damage.

“Nobody wants to be a news story,” Hayes told theCUBE. “Nobody wants to have a situation where the agent does something absolutely crazy and it’s because it’s a data issue. This is actually going to slow things down a little bit for some organizations because they need to take a step back and say, ‘Is our data really AI-ready?'”

Hayes spoke with theCUBE’s Rebecca Knight and Rob Strechay at Qlik Connect 2026, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how data quality, governance and vendor independence are creating a new path to trusted AI throughout enterprise organizations. (* Disclosure below.)

Data quality, lock-in and the race to AI-ready infrastructure

Boards are increasingly involved in data strategy, a dynamic that’s colliding directly with vendor lock-in risk, according to Hayes. The stakes are high: Contractual obligations can quietly limit what organizations are actually able to do with their most valuable asset.

“You don’t want your data to be a hostage,” Hayes explained. “You don’t want to be making decisions in your architecture that aren’t good for the business. If you choose a data platform or an AI solution, you don’t want to be making that decision because it’s the easiest because [you] already have this vendor, or it’s the easiest because they’re difficult to deal with and they already have [your] data. You need to be making these decisions autonomously based on what you want to do with the data.”

Qlik’s answer is in what can be described as “data freedom,” an architecture-agnostic approach that moves data wherever it needs to go without any contractual constraints, Hayes noted. The philosophy centers on organizations choosing data solutions based on what they want to achieve, not based on who already has their data.

“Your data is your data and we will help you get it no matter what you have to do, from where it is, to where it needs to be,” he said. “The freedom of data is really important here because you just can’t have contractual obligations or vendor lock-in issues restricting what you’re going to get out of the value of that data.”

Here is 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