Product release cycles at London Stock Exchange Group dropped from 3–6 months to 2 weeks after integrating OpenAI’s ChatGPT Enterprise and APIs across the organization. That’s a 10x improvement in time-to-market for a company that supports 40,000 customers and 400,000 end users across 190 markets.
From 6 Months to 2 Weeks: The Release Cycle Math
Max Grigoryev, LSEG’s Group Director for AI Products, put the numbers bluntly: “Historically, bringing products to market often took three to six months because of regulatory, compliance, legal, cybersecurity, and delivery requirements. Now, many of the products we are adapting for AI consumption are on a two-week release cycle.” The same speedup applies to customer requests—deployments now take roughly 4 weeks from request to production.
LSEG didn’t just bolt on a chatbot. They embedded OpenAI into every layer: thousands of employees across product, engineering, research, and operations use ChatGPT to draft reports, synthesize financial data, prototype features, and streamline client communications. Analysts now cut research time dramatically; product teams move from concept to prototype in hours.
Governance as Enabler, Not Gate
Emily Prince, Group Head of Enterprise AI at LSEG, emphasized that the rollout started with real problems and scaled responsibly. Governance came first: model evaluation frameworks, human-in-the-loop review for critical outputs, and strict data privacy controls. “We don’t think about restricting people—we think about enabling them,” Grigoryev said. That foundation let thousands of employees go live within weeks, driven by grassroots demand rather than top-down mandates.
LSEG’s clients were already using ChatGPT, which created a natural pull to integrate LSEG’s trusted data into those existing workflows. The result is a system where internal best practices scale automatically while compliance requirements stay baked in.
What This Means for Enterprise AI
The takeaway isn’t “AI is fast.” It’s that rethinking the entire workflow—not just automating individual tasks—unlocks compounding gains. LSEG saw improved cross-functional collaboration, faster information flow, and expanded innovation velocity because they challenged how work gets done, not just how tasks get executed.
That mindset shift is the real product. LSEG is now moving beyond individual productivity gains to deeper, workflow-level AI integration in research processes, product development, and client-facing systems. The 2-week release cycle is the starting point, not the ceiling.
Source: From data to decisions: how LSEG is scaling trusted AI
Domain: openai.com
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