What challenges did LSEG face before AI implementation?

Financial professionals needed faster data analysis, fewer manual steps, and greater confidence in AI-assisted decision-making. LSEG and Microsoft also had to embed governance, permissions, and data provenance so trusted financial data could be used correctly in AI workflows.

Rank#676of 3,449

Source

MicrosoftProductionEvidence: Low40/100

How LSEG and Microsoft are transforming financial services with trusted data and AI

Use case typeInvestment researchUpdated Mar 26, 2026

LSEG and Microsoft are enabling financial firms to use LSEG-licensed trusted financial data inside Microsoft 365 Copilot across apps such as Teams and Excel, as well as within customers' own channels and applications. The solution also uses MCP connectors to help users build AI agents that can access governed data and embedded context for specific financial workflows. The collaboration combines LSEG Workspace, Microsoft applications, and Copilot so professionals can analyze data faster and work with fewer manual steps.

Organization: LSEG
Industry: Finance
Location: United Kingdom
Published: March 2026

Reported outcomes

Strategic outcomes

Better decisions & insightFaster insight generationOther strategic outcomeReduced manual stepsRisk & complianceGoverned AI use of licensed financial data

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: LSEG
Provider: Microsoft
Maturity: Production
Linked source: LSEG

It also reports quicker insight generation and reduced operational friction in daily workflows

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 2 of 2

1Investment research
2Workflow orchestration

Financial professionals needed faster data analysis, fewer manual steps, and greater confidence in AI-assisted decision-making.
LSEG and Microsoft also had to embed governance, permissions, and data provenance so trusted financial data could be used correctly in AI workflows.

LSEG licensed data is enabled for use in Microsoft 365 Copilot across Teams and Excel and can also be embedded into customer channels and applications.
Users can discover LSEG data through agents built in Copilot Studio and delegate tasks to Copilot for analysis, with outputs flowing into Excel, PowerPoint, or Workspace for deeper work.
MCP connectors expose trusted data to AI agents while preserving permissions and metadata, allowing teams to prototype and automate workflows with less engineering dependency.

Technologies

Microsoft 365 Copilot Copilot Studio Azure AI Microsoft Teams Excel Word PowerPoint Outlook MCP connectors LSEG Workspace

The article says the partnership helps users analyze data faster, reduce manual steps, and make decisions with greater confidence.
It also reports quicker insight generation and reduced operational friction in daily workflows.
The approach is already delivering real impact across financial services and is designed to enable more personalized insights and more complex automation.

Architecture

LSEG-licensed data is integrated into Microsoft 365 Copilot and Microsoft applications such as Teams and Excel. Users can build agents in Copilot Studio and use MCP connectors to surface governed data with permissions and metadata. LSEG Workspace provides the underlying financial platform and the ecosystem can extend into customers' own channels and applications.

Sources & evidence1

Evidence: Low40/100Evidence strength