From data to decisions: how LSEG is scaling trusted AI

London Stock Exchange Group (LSEG) ⁠ (opens in a new window) sits at the heart of financial markets. A leading global financial markets infrastructure and data provider, it supports more than 40,000 customers and 400,000 end users across approximately 190 markets.

For years, LSEG had invested heavily in AI and machine learning to power financial models and analytics. But the emergence of generative AI introduced a fundamentally new opportunity: not just improving systems, but transforming how people interact with data, generate insight, and make decisions.

The challenge was clear. Despite advanced infrastructure, knowledge work across the organization still involved manual synthesis, fragmented workflows, and time-intensive processes that slowed insight generation and limited scalability.

Start with high-impact, low-risk use cases: Governance is critical for scaling safely for LSEG.

Invest in training and enablement: The best use cases often emerge from users themselves.

LSEG is now expanding beyond individual productivity gains to more deeply embedded, workflow-level AI applications. This includes integrating AI directly into research processes, product development, and client-facing solutions.

At that moment, OpenAI became a natural partner—bringing powerful models, intuitive interfaces, and an ecosystem already being adopted by LSEG’s customers.

LSEG approached generative AI with a deliberate strategy: start with real problems, and scale responsibly.

The company selected OpenAI based on model quality, enterprise readiness, and alignment with customer demand. Many LSEG clients were already using ChatGPT, creating a natural opportunity to integrate LSEG’s trusted data directly into those workflows.