LSEG: Initiation of Coverage

GAII Intelligence defines the AI Research & Intelligence market as software that applies generative and agentic AI to the research process of professional investors: locating candidate securities, assembling and interrogating evidence, producing written analysis with traceable sources, and monitoring positions once held. Buyers are hedge funds, long-only managers, multi-manager platforms, family offices and allocators; the economic buyer is typically the chief technology officer, the head of research, or a portfolio manager with a technology budget.

Capabilities we treat as mandatory

• Evidence retrieval at scale: the ability to search and reason across regulatory filings, transcripts and news, and across documents the client supplies.
• Source traceability: every material claim in an output must be reachable back to the passage that supports it.
• Institutional data handling: a stated position on where client data goes, how long it is held, and whether it is used for model training.

Capabilities we treat as differentiating

• Persistent state: the system remembers a thesis, a coverage list or a position between sessions and acts on it without being re-prompted.
• Workflow surfaces: delivery inside the applications analysts already use — the spreadsheet, the research management system, email and messaging.
• Owned or exclusive content: material that a competitor cannot obtain by signing the same third-party contract.
• Published evaluation: a measured, disclosed accuracy methodology rather than an assertion of quality.

This note rates LSEG's AI offering for investment professionals — Workspace AI, Teams and Excel surfaces, MCP and the data those features can reach — not the Data & Analytics division or the group as a whole. LSEG competes with Bloomberg, FactSet and S&P Capital IQ Pro among incumbents, and partners with AI-native vendors such as Rogo while competing with AlphaSense and Hebbia for research workflow.

The following are the capabilities and characteristics that, in our assessment, most distinguish LSEG within the AI Research & Intelligence market. Each is drawn from publicly documented product capability, published interviews with management, or independent hands-on review.

• Distribution: MCP in Claude, ChatGPT, Copilot Studio, Gemini Enterprise and Amazon Quick; Copilot in Excel; Databricks and Snowflake shares.
• Microsoft partnership: Ten-year alliance (2022) with native Teams, Excel and Copilot surfaces.
• Content: Reuters, I/B/E/S, StarMine, Datastream, Worldscope and exclusive Morgan Stanley aftermarket research.
• Agent traction: AI Search at 17,000 active users and Deep Research users up four times in a quarter (July 2026).
• Identity controls: Microsoft Entra SSO with Conditional Access and SCIM provisioning.
• Commitment: A ten-year Microsoft alliance and a dedicated Group Head of Enterprise AI.

The following are factors that prospective clients should weigh, and areas where our public review did not find sufficient evidence to reach a settled view. Several are common across vendors at this stage of the market and are not specific to LSEG. We encourage prospective clients to raise each of them directly with the company; we have done the same, and will update this note as answers arrive.

• Late native AI: AI Search reached general availability only in June 2026, with some citations acknowledged as missing.
• Disclosure: No public SOC 2 or ISO 27001 evidence, no-training commitment, AI subprocessor list or MNPI controls located.
• Client data: No document upload or client data in Workspace AI; only via Databricks or Snowflake.
• Expert content: None.
• Cost layering: Deep Research add-on, use-case licences for data in AI applications and MCP usage charges.
• Evaluation: No published accuracy measurement.

LSEG's AI programme rests on a ten-year Microsoft partnership signed in December 2022, which moved Workspace to Azure and put LSEG data into Teams, Excel and Copilot. Emily Prince leads enterprise AI; the first generative Workspace features went to pilot in 2024.

Since October 2025 LSEG has launched MCP access in Copilot Studio, Claude, ChatGPT, Amazon Quick and Gemini Enterprise, and in 2026 added Deep Research (June), AI Search general availability (June) and Company Intelligence (July). By July 2026 AI Search had 17,000 active users and Deep Research users had quadrupled in a quarter (company).

Company-reported figures are shown as such and are not independently verified. Verification is carried into the vendor questionnaire.

LSEG offers AI in Workspace and Teams and distributes data to external AI platforms. Figure 2 sets out our assessment of how it maps onto the investment workflow.

AI Search

Natural-language search over data and content with citations (general availability June 2026).

Deep Research

Multi-step agent with charts and code generation; premium add-on (June 2026).

Company Intelligence

Structured company reports exportable to PDF and Word (July 2026).

MCP and Microsoft surfaces

MCP in seven-plus AI platforms; Workspace for Teams; Copilot connector in Excel.

Scope of the product today

We did not locate client document upload in Workspace AI, expert content, published evaluation or a public trust centre.

LSEG describes an open, model-agnostic approach using OpenAI and Anthropic models, with simple prompts routed to cheaper models; it has no proprietary model. A semantic finance data model, deterministic calculations and entitlement checks sit beneath AI Search and MCP.

No accuracy evaluation is published, and AI Search release notes acknowledge missing citations in some cases.

Content spans Reuters news, filings, transcripts, I/B/E/S estimates, StarMine, Datastream, Worldscope, Lipper and aftermarket broker research, including exclusive Morgan Stanley distribution — 33 petabytes in all.

Transcripts are not yet available over MCP, and expert content is not offered.

LSEG fits consensus, macro and modelling work, delivered wherever the analyst works — Workspace, Teams, Excel or an external assistant.

Idea generation and monitoring are query-led rather than agentic.

LSEG uses Microsoft Entra for SSO with Conditional Access and SCIM, enforces entitlements on AI and MCP access and describes audit-ready outputs and lineage; the Teams app holds Microsoft 365 Certification. Figure 3 sets out what our public review located.

We would encourage buyers to request attestation reports, a no-training commitment, AI providers and MNPI controls.

The offsetting factors are Microsoft Entra identity controls and entitlement checks on AI and MCP access.

Pricing is not published. AI Search is included under a fair-use allowance, Deep Research is a premium add-on, and data used in AI applications needs a use-case licence plus usage charges.

Buyers should map the full licence stack before adoption.

LSEG sits in the Emerging quadrant of the matrix, held back by native AI maturity, disclosure and cost layering.

GAII Research & Intelligence coverage plus the Established Platforms group (Bloomberg, FactSet, LSEG, S&P Global MI, MSCI), 21 October 2026. Established Platforms are rated only on their AI offering for investment professionals and the data it can reach — not on company size or non-AI products.

11.1 Where LSEG is strongest relative to peers

• Against other incumbents, on breadth of AI-platform distribution.
• Against AI-native vendors, on consensus and macro data.
• Against Bloomberg, on Microsoft surfaces.

11.2 Areas of narrower functional focus

LSEG has built distribution ahead of native agents and disclosure.

• Native AI: general availability only in mid-2026.
• Disclosure: no trust documentation.
• Content: no expert content.
• Commercial: layered licences.

Scores are on a 0–10 scale. Each dimension score is the mean of its sub-criteria, and the GAII Overall Score is the weighted mean of the six dimensions. The detailed sub-criteria scores that build each dimension are set out in Appendix A.

These are the areas where our public review did not find sufficient evidence to form a settled view. We have put them to the company and will update this note when they are answered. Prospective clients may find them a useful agenda for their own evaluation call.

• SOC 2 and ISO 27001 reports for Workspace AI.
• A no-training commitment.
• AI model providers and subprocessors.
• MNPI controls.
• Accuracy evaluation.
• Citation completeness since general availability.
• Client document ingestion in Workspace AI.
• Transcripts over MCP.
• Deep Research and use-case licence pricing.
• Workspace user count.
• Expert content plans.
• Microsoft board representation.

This note is an assessment of a vendor against a defined framework, not a recommendation to buy or to decline. The following are the considerations we would put at the centre of an evaluation of LSEG specifically.

If you are a fundamental equity manager

• Use LSEG data inside your existing assistant via MCP.
• Test Deep Research before buying the add-on.
• Check citations on AI Search answers.

If you are responsible for technology or vendor risk

• Open with Figure 3; request attestation reports.
• Map use-case licences for AI use.
• Confirm no-training terms.

If you are assessing the category rather than the company

• Incumbents compete on distribution into AI platforms.
• Microsoft surfaces matter for Copilot-only firms.
• Licensing for AI use is a new cost line.

Each dimension score in Section 12 is the mean of the sub-criteria below.