of the most enjoyable things I get to do in my job are when I travel out to Microsoft and we discuss product roadmaps at a very early phase, where it is still early enough that we can provide meaningful input. I have not had this kind of relationship with any other partner.” Some of the central strategic questions the partnership has had to answer are deceptively simple: when should LSEG data be embedded into existing tools, when should existing surfaces be enhanced and when does something entirely new need to be built? The answer is to start from where the customer already is. “We want to embed data into Microsoft Teams, Copilot Studio, Foundry, Claude, ChatGPT – giving users the same capabilities and experience they are familiar with and letting them choose their preferred endpoint,” says Esmiley. “We are not saying to customers you need to change your whole infrastructure to adopt this new application. This reflects a broader shift in how organisations are redesigning operating models for the AI era.” Byrne frames it as a philosophy that predates AI but has been dramatically accelerated by it. “In a pre-AI world I would have said it was important for LSEG to meet customers wherever they want to consume our data,” he says. “AI has only accelerated and expanded that problem statement.” Centralising data in Microsoft Fabric before distributing it flexibly has become the architectural answer to a world where, as Byrne puts it, “nobody knows what the flavour of the month will be a year from now.” Crucially, though, distribution alone is not enough. “It is not just about getting data to where clients want it but delivering it in a format that is ergonomic for native AI capabilities: business glossary definitions, data model semantic definitions, responsive APIs and model context protocol (MCP) servers.” This approach aligns with emerging best practices for building AI-ready operating models and integrating data into modern workflows. Before any of that AI-era distribution could be contemplated, however, both organisations needed to build governance foundations capable of bearing the weight of financial services regulation. Data lineage – the ability Photo: iStock/miniseries INTERVIEW “ We are not saying to customers you need to change your whole infrastructure to adopt this new application” MARC ESMILEY, MICROSOFT 86
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