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    UK and Ukraine Sign Strategic AI Deal to Develop Battlefield Technology

    By Art RyanAugust 25, 20260

    The United Kingdom and Ukraine are taking their technology partnership deeper into artificial intelligence. On…

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    Home » LSEG Brings Market Data Into ChatGPT
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    LSEG Brings Market Data Into ChatGPT

    Art RyanBy Art RyanDecember 5, 2025No Comments3 Mins Read
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    London Stock Exchange Group (LSEG) announced on Wednesday (Dec. 3) a new collaboration with OpenAI to bring LSEG’s licensed financial data and analytics directly into ChatGPT, expanding the exchange operator’s push to deliver artificial intelligence ready data across financial markets.

    The integration will begin the week of Dec. 8 and will allow users with LSEG credentials to access Financial Analytics content, real-time market data, research and news from within ChatGPT through a connector built using the Model Context Protocol. LSEG said the approach will let clients query its datasets inside a conversational interface without switching systems.

    LSEG said about 4,000 of its employees will gain immediate access to ChatGPT Enterprise as part of the collaboration to support internal research and workflow automation. The company described the partnership as an extension of its data-distribution strategy, which aims to make its content available in any AI environment that clients use. LSEG said it plans to expand the data categories available in ChatGPT after the initial launch.

    The new partnership follows an earlier collaboration between LSEG and Microsoft that PYMNTS reported in October. In that agreement, LSEG enabled banks and financial institutions to connect licensed LSEG data to Microsoft’s AI tools, including Copilot Studio, through the same MCP standard now used in the OpenAI connector. PYMNTS reported that the Microsoft partnership allowed customers to build and deploy AI agents with direct access to LSEG’s historical datasets, pricing information and analytics pipelines.

    LSEG said the OpenAI partnership will fit into the same “LSEG Everywhere” framework introduced earlier this year, which commits the company to making its data available across multiple AI platforms, including third-party model providers. Emily Prince, LSEG’s Group Head of AI, said the integration combines the security of enterprise AI platforms with the scale and depth of LSEG’s financial content. OpenAI Chief Revenue Officer Ashley Kramer said the connector will support more complex financial queries and faster analysis for users who rely on LSEG data. The announcement comes as more businesses are utilizing generative AI in business operations.

    OpenAI, onstage Wednesday at the FT Global Banking Summit, said European financial firms are accelerating adoption as generative AI becomes the operating system shaping fraud detection, investment analysis, and lending decisions. The company highlighted new enterprise customers, including Revolut, Allica Bank, Hg, EQT, and Permira, along with impact data from Zopa and OakNorth.

    Revolut is using GPT 5 to strengthen financial crime controls and customer support. Allica said it is cutting lending assessment times. Zopa is reviewing about 40,000 customer interactions each month. OakNorth has automated workflows across the company. EQT and Permira reported near universal employee adoption and portfolio level revenue impact.

    The AA and LSEG also announced plans this week to use ChatGPT Enterprise. LSEG said it will roll out ChatGPT Enterprise to 4,000 employees as part of the same OpenAI collaboration that brings its data into ChatGPT through the MCP connector.

    Matt Weaver, OpenAI’s EMEA solutions engineering lead, emphasized that AI has moved from pilots to production and said regulated industries are leading adoption. He said financial firms are showing how governance, strategy and platform design allow highly regulated institutions to scale AI safely.

    LSEG’s launch of Financial Analytics within ChatGPT is the first phase of a broader rollout planned across 2026. The company said its long-term goal is to make its licensed datasets accessible to clients through any AI interface that supports enterprise access control, and it plans to expand coverage to additional asset classes and research tools as the collaboration evolves.

    Source: https://www.pymnts.com/
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