Morningstar rolls out agentic AI platform built on its research

Morningstar is updating its flagship research platform around artificial intelligence agents, betting that investment professionals who already use AI will pay for tools grounded in independent data rather than general-purpose chatbots.

The Chicago-based firm has announced the rollout of a new agentic AI platform, Morningstar Direct AI, to users worldwide.

According to a Wednesday announcement from Morningstar, Direct AI has a new browser-based interface and three agents capable of handling analysis that until now meant toggling between tools, relying on in-house expertise or building manual workarounds.

"AI and agents are only as valuable as the data that powers them," said Scott Brown, president of the Direct Platform at Morningstar. "With Direct AI, we're putting the full breadth of our independent research, data, and insights into agents that fit naturally into clients' workflows."

The platform's product development agent is targeted towards asset managers deciding which funds to launch and how to position them. Drawing on Morningstar's fund-flow data and category analysis, the firm said it can field questions such as which categories have strong investor demand but few competitors, or the time it took for similar products to reach $1 billion in assets.

Another agent, focused on distribution, is designed to help sales and marketing teams trying to get a fund onto a firm's approved list or into a model portfolio. It can look at an existing model – including ones that mix public and private securities – find gaps for a fund to potentially fill, and simulate how the fund would change a model.

The platform also includes a manager research agent to support due diligence teams. Using the same framework as Morningstar's analysts, it is capable of examining whether a fund's trading patterns have shifted, which market conditions have historically helped or hurt returns, and other potential questions.

The agents rely on Morningstar's ratings, research and data. The firm says it employs more than 1,100 research analysts globally to support that body of knowledge, which covers millions of securities across funds, stocks, bonds and other products.

Morningstar said it is also making its research available inside Claude, Microsoft Copilot and ChatGPT so users can reach it from whichever AI tool they use.

Read more: ChatGPT launches embedded Morningstar and Pitchbook apps to compete directly with standalone AI investment research tools?

Morningstar's Direct AI launch came a day after its subsidiary Morningstar Wealth announced it would distribute its Morningstar Public/Private Select Series model portfolios through Envestnet, with plans for initial availability this month.

Under the new partnership, advisors on Envestnet's enterprise platform will be able to use the models through its Fund Strategist Portfolios program. Morningstar Wealth keeps responsibility for asset allocation, manager selection, portfolio construction and ongoing oversight. Envestnet provides the technology that puts the models into client accounts.

Morningstar Wealth first unveiled the series in June, just as the race to package public and private markets into model portfolios was speeding up among large asset managers.

"The value of private-market exposure depends on how it fits within the whole portfolio," Morningstar CEO Kunal Kapoor said. "By pairing [our] investment approach with Envestnet's implementation capabilities, we're giving advisors a more practical way to manage public and private investments together."

Read more: Envestnet extends investment offerings with new alts model portfolios

Envestnet CEO Chris Todd said his firm's platform "automates the trading, rebalancing and tax management behind every account, so advisors can put these strategies to work at scale and keep each portfolio aligned to a client's goals."

Morningstar's own advisor research suggests demand exists for both offering. In its 2026 Investor Perspectives Advisor study, the firm found 80% of U.S. advisors now use AI in some form, up from 67% a year earlier. While 48% said AI had meaningfully improved their efficiency. However, only 18% rated AI tools as highly reliable for investment recommendations or portfolio decisions.

In the same survey, 40% of advisors said they now offer private-market products, up from 35% in 2025. But the survey also revealed challenges around fees and fee transparency (cited by 46% of advisors), limited liquidity (41%), and limited visibility into underlying holdings (35%).