Data quality, and data freedom, are fundamental to the success of AI

Data quality is emerging as a key factor that separates business AI projects that produce results from those that do.

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

“No one wants to be the subject of the news,” Hayes told the CUBE. “No one wants to have a situation where an agent does something crazy and it’s because it’s a data problem. This will actually slow things down a bit for some organizations because they need to step back and say, ‘Is our data really ready for AI?'”

Hayes spoke with CUBE’s Rebecca Knight and Rob Strechay at Qlik Connect 2026, during an exclusive broadcast on CUBE, SiliconANGLE Media’s live streaming studio. They discussed how data quality, governance and vendor independence are creating a new way for AI to be trusted across business organizations. (* Disclosure below.)

Data quality, lock and race for AI-ready infrastructure

Boards are heavily involved in data strategy, a dynamic that is directly at odds with the risk of vendor lock-in, according to Hayes. The stakes are high: Contractual obligations can quietly limit what organizations can actually do with their most valuable assets.

“You don’t want your data to be held hostage,” explains Hayes. “You don’t want to make decisions about your architecture that aren’t right for the business. If you’re choosing a data platform or an AI solution, you don’t want to make that decision because it’s the easiest one.” [you] they already have this seller, or it is very easy because it is difficult to deal with them and they already have them [your] data. You need to make these decisions independently based on what you want to do with the data. “

Qlik’s answer lies in what can be described as “data freedom,” an architecture-agnostic approach that moves data wherever it needs to go without contractual constraints, notes Hayes. The philosophy focuses 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 something indeed it is important here because you just I won’t be for the contract commitments or a merchant lock-in the middle news to limit what you I’m going to find out outside of i value of that data.”

Here is the full video interview, part of SiliconANGLE and CUBE for Qlik Connect 2026:

(* Disclosure: TheCUBE is a paid media partner of Qlik Connect. Qlik, the CUBE’s event sponsor, or other sponsors have editorial control over content on TheCUBE or SiliconANGLE.)

Photo: SiliconANGLE