Trusted standards, now built for AI.
AI built on a foundation you can trust.The data, models and research global markets rely on, now driving a new generation of AI capabilities.
AI is reshaping how investors work, and MSCI is helping to drive that shift. For decades, we've provided the data, standards and methodologies that connect global market participants. Today we're applying that expertise to build AI solutions that help investors move with greater speed, confidence and clarity.
We provide the common language of global investing — the standards and methodologies markets rely on to connect and compare. With AI, we put our expertise to work, reducing friction, accelerating collaboration and deepening shared understanding.
Data is at the heart of what we do. With AI, we can help you draw more value from MSCI’s proprietary data and analytics, so you can assess risk, monitor performance, evaluate opportunities and navigate challenges with confidence.
MSCI content is embedded directly into the platforms, workflows and AI services you rely on, so teams can access what they need without leaving the tools where decisions get made.
AI in actionPurpose-built for every stage of your investment process
Query MSCI inside your platform
Bring MSCI into your AI workflows through one gateway. The MSCI Connector works in Claude, ChatGPT, Copilot and MSCI ONE.
Explore indexes conversationally
Ask plain-language questions about performance, constituents, exposures and methodology across more than 68,000 indexes with MSCI IndexAI InsightsTM
Scale your risk management
Easily embed risk insights across your investment process to create efficiencies and reshape workflows with AI Portfolio Insights.
Analyze private markets with AI
Apply AI across the private asset lifecycle, from due diligence to portfolio oversight, turning fragmented data into decision-ready insight.
Identify location-specific risk
Quantify asset-level physical and nature risk exposure and financial impact where it matters scaling AI for data collection with GeoSpatial Asset Intelligence.
The MSCI differenceThe data foundation for AI in investing
AI built on MSCI starts from a different place: the data, standards and methodologies that global markets already run on.
$21 trillion
AUM benchmarked to MSCI indexes.1
$50 trillion
Enterprise assets managed on MSCI risk analytics platforms.2
$17.8 trillion
In private asset investments covered.3
55+ years
Experience helping investors turn market complexity into investment insight.
Research and insightsOur latest research on AI and investing
Investment Trends in Focus: Midyear Update 2026
AI, not geopolitics, drove markets in 2026’s first half. But the gains were narrow, and the equity risk premium has hit its lowest point since the dot-com era.
How AI Becomes Investment Grade
For institutional investors, competitive advantage will arise less from AI models themselves than from the quality of the data, methodologies and governance that support them.
Scenario Analysis: The AI Supply Chain Under Stress
Geographic diversification across Korea, Taiwan and the Netherlands may mask a shared dependence on hyperscalers’ AI capital spending. Duration may offer a more reliable hedge than geography does.
Have questions about AI at MSCI?
Our data is structured, validated and traceable to its source, with accuracy and provenance verified by human experts. That means your AI works from a base that’s clean, consistent and auditable. And because our data flows directly into the platforms and environments where you already work, it's ready to use without reformatting or manual preparation.
See what MSCI AI can do for you.
About Us
Learn more about us — and how we work to build a culture of innovation and help clients across the globe power better decisions.
1 Assets under management (AUM) as of Dec. 31, 2025, reported on or before March 31, 2026, using data from eVestment for active institutional funds and Morningstar for active retail funds. Equity ETF values were based on data from Refinitiv and MSCI. In addition, AUM includes indexed assets using available internal data. AUM includes notional open interest in futures and options using internal data from MSCI. Active retail funds include open-ended funds, closed-ended funds and insurance product funds. Active institutional AUM includes separate/segregated AUM, pooled/commingled AUM and mutual fund institutional AUM. AUM includes equity and multi-asset class funds and excludes feeder funds and funds of funds. Where an MSCI index is only a portion of a multi-asset class (MAC) or other hybrid or blended benchmark, AUM reflects the Morningstar data which allocates all AUM to the primary benchmark used in the MAC/hybrid/blended benchmark (which may undercount or overcount AUM linked to the MSCI portion depending on its weight in the benchmark). For funds where AUM was not reported as of Dec. 31, 2025, the previous period AUM was utilized as an estimate.
2 As of January 2026. Represents average number of Analytics client positions processed in rolling seven-day period.
3 Covers RiskManager and BarraOne platforms. As of December 31, 2025.