US AI-Driven Investment Intelligence Raises the Stakes for European Rating Agencies

The launch of Morningstar and PitchBook applications within ChatGPT marks a significant escalation in the global competition for investment intelligence. By integrating proprietary financial data directly into AI-driven workflows, the US-based firms are redefining how investors access, analyze, and act on market information—and in doing so, they are widening the gap European rating agencies must overcome to remain competitive.

According to the announcement, the new Model Context Protocol (MCP) app integrations allow licensed users to access “proprietary public and private market data and insights securely … via natural language prompts” directly within ChatGPT (Morningstar & PitchBook, 2025). For investors and financial professionals, this removes friction between data, analysis, and decision-making, embedding trusted research directly into conversational AI environments.

Tom Van Buskirk, Executive Vice President of Technology and Engineering at PitchBook, underscores the strategic logic behind this move:

“Great AI requires great data to build truly exceptional customer experiences, and Morningstar and PitchBook have long been recognized for their investing intelligence quality and independence” (Van Buskirk, PitchBook).

By pairing OpenAI’s large language models with analyst-backed data, Morningstar and PitchBook aim to deliver not just automation, but confidence. Van Buskirk adds that the integration gives users “analyst-backed data and insights directly inside their Morningstar and PitchBook apps in ChatGPT,” enabling “smarter decision-making.”

From Research Providers to Intelligence Infrastructure

The announcement reflects a broader strategic ambition. Morningstar describes its objective as becoming “the indispensable intelligence layer for investing,” positioning itself not merely as a data provider but as foundational infrastructure for the investment ecosystem. This ambition is reinforced by a growing network of AI partnerships, including integrations with Anthropic’s Claude, Perplexity Finance, Microsoft Copilot Studio, and other AI-native platforms.

Adam Wheat, Head of Data & Research Solutions and CTO for Morningstar’s Direct Platform, frames this shift as structural rather than incremental:

He emphasizes that competitive advantage increasingly lies in the combination of machine intelligence with human expertise:

“Morningstar and PitchBook are leading into the era of trusted AI by uniting powerful machine intelligence with human-backed insight.”

This hybrid model—AI at scale, governed by human analysts and independent standards—is central to the firms’ approach. It enables faster coverage expansion, improved reliability, and the creation of new proprietary insights across public and private markets.

The Competitive Challenge for European Rating Agencies

For European rating and research agencies, this development highlights several structural challenges.

First, data scale and depth. Morningstar and PitchBook operate vast proprietary datasets spanning public markets, private capital, debt securities, and real-time global market data. European agencies, often more fragmented and regionally focused, struggle to match this breadth—particularly in private markets, where PitchBook has established itself as a global reference.

Second, AI distribution and partnerships. US firms are embedding their data directly into dominant AI platforms where users already work. European competitors rarely enjoy comparable access to global AI ecosystems, limiting their visibility and relevance as AI becomes the primary interface for financial research.

Third, product integration and user experience. Morningstar and PitchBook emphasize seamless, end-to-end workflows: “access analyst-backed ratings, research, and investing intelligence … without leaving ChatGPT.” Many European agencies still deliver research in siloed platforms or static formats, making it harder to compete with conversational, real-time intelligence.

Finally, investment capacity and strategic risk tolerance. The scale of AI integration described—enterprise-grade security, human-in-the-loop governance, and continuous product innovation—requires sustained investment and a willingness to experiment. European agencies, often operating under tighter regulatory and budgetary constraints, face higher barriers to executing comparable strategies.

A Widening Transatlantic Gap

The Morningstar–PitchBook integration illustrates how AI is accelerating consolidation around a few global intelligence providers. By positioning themselves as the “investor-first intelligence layer” that enables “agentic workflows, evolving investment strategies, and new benchmarks” (Wheat, Morningstar), these firms are shaping not only products, but market expectations.

For European rating agencies, the challenge is no longer just analytical credibility—it is technological relevance, ecosystem access, and the ability to embed trusted European perspectives into the AI-driven infrastructure that is rapidly becoming the default interface for global finance.

Source

Morningstar, Inc. & PitchBook (2025): Morningstar and PitchBook Bring Trusted Investing Intelligence to Apps in ChatGPT, Business Wire press release, Chicago & Seattle.