Artificial intelligence promises to transform financial services — but data trust remains the single greatest barrier between ambition and adoption.

Ataccama’s Larry Hunt (right) discusses AI, trusted data and governance with theCUBE.

In the past, banks focused primarily on people, processes and technology. Today, that rubric has changed; data now stands alongside those pillars — not only as a compliance utility, but as an engine for competitive differentiation and innovation, according to Larry Hunt (pictured), field chief data officer for financial services at Ataccama.

“The data conversation has shifted from where it’s been historically, which was an IT black box that nobody understood, to a conversation with CEOs and boards of what they can do with their data to glean value for the company,” Hunt said. “A lot of that has been accelerated in recent months with the evolution of AI, and what companies think they can do with it to further drive value for their companies.”

Hunt spoke with theCUBE’s Rob Strechay for an exclusive conversation with theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed insights from the company’s just-released “2025 Data Trust Report: Financial Services Edition” and why governance, sustainability and data trust must sit at the heart of every AI strategy. (* Disclosure below.)

Data trust positions governance as an enabler, not an obstacle

Many leaders struggle to balance AI ambition with governance, risk and regulation. The ones that succeed treat governance as an enabler. With tools that can classify, monitor and audit data, organizations can maintain compliance dynamically, rather than reactively, according to Hunt.

“Your governance is an enabler to build trust,” he said.  “The other piece of that is leveraging the AI to do the governance aspect of it. One thing that the AI narrative has over some of the other things we’ve tried to adopt historically is that people have already accepted that AI is going to happen.”

When governance programs stumble, it’s often because they’re sold as bureaucracy rather than business value. Success depends on connecting governance to real metrics — cost reduction, efficiency and risk mitigation, Hunt added.

“Most governance programs fail by trying to sell a governance program,” he said. “The governance program is really to enable business outcomes, so if you’re not connecting that governance program to a business outcome, the audience that’s receiving it is not going to understand the why, and the why is super important.”

Despite the widespread enthusiasm, genuine AI adoption lags behind expectations, according to Hunt. According to Ataccama’s recent research, 99% of financial services firms are piloting AI projects, yet only 3 to 4% are seeing real outcomes.

“One of the key blockers and the ability to do that is data trust,” he said. “In addition to that, having the right people, the right infrastructure and the right technology. But even in my own experience, a data dearth causes companies not to be able to deliver key use cases — something as simple as scripts for a call center that an element could use to summarize that the data didn’t exist, so we weren’t able to achieve those outcomes for those models.”

Importantly, legacy technology continues to drag down the progress of data transformation. Years of mergers and acquisitions have left banks with fragmented, federated systems. AI, however, is expediting that modernization. The move to the cloud, while complex, helps organizations manage compute and storage at scale. The future lies in data products and domains — a more unified approach that de-risks environments and improves interoperability, according to Hunt.

Here’s theCUBE’s complete video interview with Larry Hunt:

(* Disclosure: Ataccama sponsored this segment of theCUBE. Neither Ataccama nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE