Morningstar on Tuesday published a new investor Q&A outlining how it plans to monetize AI-driven workflows, defend the value of its core platforms and capitalize on growing demand for private-market data.

The most important theme was pricing. Morningstar said traditional seat-based models may become less useful as AI allows customers to do more work with fewer employees. The company is therefore experimenting with value-based and consumption-based pricing, where fees are tied more closely to the economic value or volume of data consumed rather than simply the number of users.

That shift could be particularly important for PitchBook. Customers are increasingly accessing PitchBook data through APIs, large-language-model integrations and MCP connectors, and Morningstar said it wants pricing to capture value across all of those channels. PitchBook is already testing connector-only seats and a direct MCP product expected to use consumption-based pricing.

Importantly, Morningstar is not giving away its most valuable PitchBook intellectual property. Tools such as VC Exit Predictor, Manager Scores and Valuation Estimates remain exclusive to the PitchBook platform, where management believes switching costs are highest. That distinction could help preserve the platform’s pricing power even as raw data becomes easier to access through AI interfaces.

AI is also already creating a new revenue stream. Morningstar said LLM providers pay PitchBook for certain essential data, while existing subscribers can currently access premium connectors through platforms including Claude and ChatGPT at no additional charge. Management indicated it retains the option to charge separately for those connectors later.

The company also pushed back against concerns that AI investment is materially damaging profitability. Direct’s Q2 adjusted operating margin slipped to 45.2% from 46.0%, while PitchBook’s fell to 30.3% from 31.7%. Morningstar characterized the declines as modest and largely reflective of normal investment cycles.

Still, investors should not necessarily expect AI efficiencies to flow directly into margins anytime soon. PitchBook said productivity gains from AI-powered data gathering have largely been reinvested into broader coverage and new datasets, rather than harvested as cost savings. That suggests the near-term thesis remains growth and moat-building rather than margin maximization.

Underlying operating trends were relatively encouraging. Morningstar said the recent acceleration in organic growth at PitchBook and Morningstar Direct was not driven by unusually easy comparisons or seasonality. PitchBook license growth continues to come primarily from deeper penetration among existing private-equity, asset-management and commercial-banking customers, although venture-capital and corporate clients remain softer.

Morningstar Direct showed a similar pricing-and-mix story. Licenses were roughly flat year over year, yet organic revenue grew around 7%, driven by higher revenue per license and expansion within Reporting Solutions. Management cautioned that investors should not treat revenue per license as a pure pricing metric because customer mix, usage and contract structures also affect the number.

Another increasingly important opportunity is the convergence of public and private markets. Morningstar said private-market-related ratings generated roughly 25% of Morningstar Credit’s ratings revenue in 2025, while PitchBook continues to expand private-credit datasets and analytics. Morningstar Wealth, Direct, Retirement and Indexes are also launching products tied to private assets and semiliquid funds.

Capital returns remain another supportive factor. Despite the recent CRSP acquisition, Morningstar said it prioritized repurchases in 2026 and had reduced shares outstanding by 5.6% year to date through June, while maintaining its broader priorities of investing for growth, pursuing acquisitions and increasing the dividend over time.

Overall, the Q&A reinforces Morningstar’s broader investment case: the company is betting that AI will increase the consumption and usefulness of its proprietary financial data rather than commoditize it. The key question for investors is whether Morningstar can successfully translate that increased usage into new pricing models without weakening the highly profitable subscription businesses that built the company.