The rise of interoperable and multi-cloud data infrastructure
The move to the cloud has been one of the key trends in in the financial services space over the last decade, but companies are now finding that optimal solutions require integration of multiple cloud platforms, says Neill Clark, Managing Director and Head of State Street Associates EMEA. “Five years ago, I would have said the key is to get all of your data on a cloud – ideally a single cloud – and once you’ve done that, you’ve got a set of cloud-native tools and you’re good to go,” says Clark.
“Now the notion of a multi-cloud strategy plus on-prem makes more sense. The reality is everyone ended up multi-cloud by default because they couldn’t get to one cloud. Now it’s the right choice to make, because new tools are coming out all the time and computing costs vary.”
Colette Garcia, Global Head of Enterprise Data Real Time Content at Bloomberg, confirms that this approach aligns with how firms are striving to balance flexibility and precision in their data strategies. “That resonates with us – getting you the data wherever you need it, cloud-agnostic, on-prem-agnostic. It’s the quality of the data and being able to deliver it wherever you need it,” she says.
Integration of AI into investment and research workflows
Another growing trend experts point to is the integration of agentic AI into core areas of business, including investment research and portfolio management. The goal is not to eliminate human insight and judgment, but to enhance it through automated data retrieval.
According to Grégoire Dooms, Head of Data Research & Development at Systematica, AI enriches the information sets that analysts and portfolio managers can incorporate into their decision-making. “AI has completely lowered the bar for access and scale of processing unstructured data – text data,” says Dooms. “It is enabling us to build feature-extraction pipelines that are sector-specific or asset-specific and scale them tremendously.”
State Street’s Clark adds that broader data plus natural language processing tools have significantly enhanced his organization’s research product. “We’ve seen significant metric improvements: 60% better measurement of some macro criteria, 20–30% better prediction outcomes in certain use cases,” he comments. “It’s a meaningful revision in how you can access unstructured data.”
Dawn of a new era for explainable and real-time data access
AI capabilities have revolutionized the relationship between financial services organizations and their clients, allowing firms to share data and insights with clients in real-time. “We’re experimenting with open-architecture data sharing with our clients—with no barriers at all,” said State Street’s Clark.
“You’ve still got to assemble the control around it, with real-time access to data at a moment of your choosing, in a format of your choosing, integrated and delivered in a way that you can integrate with your other data sets. That feels like the way we’ll be exchanging information with our clients in the future, somehow.”
Notably, as AI’s capabilities grow, companies have to continually upgrade the guardrails that ensure regulatory compliance and ethical practices, turning strong data strategy and governance into a competitive advantage. And in a fast-approaching future where AI-enabled models may make investment decisions without human input, the need for these controls becomes even more critical.
Keeping up with a fast-changing environment
Technological capabilities are changing so fast that it’s hard to predict what AI will look like in a month, let alone a year or five years out. However, experts agree that technology already spreading into many aspects of the financial services industry would only become more ubiquitous.
“It’s not really about who’s going to use AI and who’s not, and who’s going to get left behind,” says Bloomberg’s McManus. The question really becomes: Who’s going to use it in the most intelligent way? Who’s going to be thoughtful, measured, and really understand how to derive real value from the AI they develop.
Explore how Bloomberg is using AI to deliver actionable insights that empower you to move faster, work smarter and achieve better results here. Learn more about Bloomberg Enterprise Tech & Data solutions here.
Insights in this article are based on panels and fireside discussions at the Enterprise Tech & Data Summit held in London in November 2025.
