Since the public launch of ChatGPT just over three years ago in late 2022, the general consensus that's formed around the app is that while it can reasonably replicate or summarize text in a human-sounding way, it doesn't necessarily analyze or interpret data very well. This is true for highly technical domains such as tax and law, where there's still a very real possibility of ChatGPT misinterpreting areas of the tax code or simply hallucinating (i.e., making up) sections of the law or case histories. But it's also true when it comes to numbers: While ChatGPT can do some basic math with two- or three-digit numbers, it struggles with bigger numbers and more complicated equations to the point that it's hard to trust it for any kind of real data analysis.
Which has meant that ChatGPT has typically not been a particularly good tool for doing financial-related analysis such as analyzing sequences of returns or crunching company financial data. While asking it for, say, the trailing 10-year performance of the S&P 500 will generally yield an accurate result, that's not because it's analyzing the raw price and dividend data from the index and calculating the compound total return over the last 10 years; instead, it's just scraping the web for publicly listed information that matches the request and pulling in the result from websites like YCharts. And so to the extent that the answer to a numbers-related question is on a public website somewhere (e.g., for returns of major market benchmarks), ChatGPT can be reasonably expected to bring in the correct result (though it's still always worth checking against the original source just to be sure). But when it comes to information that's not publicly listed – such as more proprietary analytics that might be behind a paywall, or private company information that isn't filed publicly with the SEC – it's harder to rely on ChatGPT to come up with a result worth trusting.
It's notable, then, that this month Morningstar announced that it has launched two new apps within the ChatGPT platform: One providing access to Morningstar's own public markets data (including its popular fund ratings, research, and analyst reports), and one with similar access to its subsidiary Pitchbook's research and intelligence in the private markets space.
The key aspect to this deal is that it gives access to users within ChatGPT of the proprietary data and research held by Morningstar and Pitchbook that isn't available on the open web. Notably, in order to use the apps, users must still be subscribed to Morningstar and/or Pitchbook, so this isn't necessarily about making that information "free" to anyone using ChatGPT. But it does make it so that Morningstar and Pitchbook subscribers who are users of ChatGPT, and who would value its chatbot interface and ability to save custom models for repeatable workflows, can plug their Morningstar data into the app without having to switch over to the Morningstar platform itself.
The news also shows that for companies that generate unique and proprietary information (e.g., investment research and analysis), and who don't list that information out on the public Internet where bots like ChatGPT can scrape it into their models, there's a real business opportunity to monetize that information by licensing it to ChatGPT and the like. Even though both Morningstar and Pitchbook have their own in-house AI tools within their respective platforms, there was enough of a demand for their data to also be available in ChatGPT that it made sense to set up this integration. Now Morningstar gets to charge for both the data, and for the privilege of having it available on the user's platform of choice.
At the same time, this news may not be so good for other third party investment research tools. The last few years have quietly seen an explosion in the number of AI investment research tools, from Boosted.ai to Fiscal.ai to Financial AI to Qdeck. Which has in part been a response to the fact that general-purpose tools like ChatGPT have been so unreliable for investment research and analysis, creating an opportunity for these companies to build their own front-end solutions pairing their own proprietary investment analytics with an LLM interface (perhaps even using OpenAI's own ChatGPT models). But now there's less reason to buy a third-party app if users can get reliable investment data from Morningstar within the ChatGPT interface itself.
But the key point is that while apps like ChatGPT have largely "figured out" the open (i.e., non-paywalled) internet, and can pull information from almost anywhere to provide an answer to a user's question (though the reliability of that answer still varies depending on how much interpretation is left up to the LLM), there's a whole world of private information that's been mostly walled off from ChatGPT and its ilk. Nearly every website requiring a login, from proprietary research sites to banking and financial apps, has information that has yet to be scooped up into LLM models – leaving the question of what other information the AI companies would like to pay for to have access to within their apps, and who stands to get paid for it?
This article first appeared on the Nerd’s Eye View at Kitces.com at https://kitc.es/advisortech-jan2026, and has been reprinted here with permission.
Ben Henry-Moreland
Ben Henry-Moreland is a Senior Financial Planning Nerd at Kitces.com, where he specializes in writing and speaking on financial planning topics including tax, practice management, and technology. He also co-authors the monthly Kitces #AdvisorTech column. Drawing from his experience as a financial planner and a solo advisory firm owner, Ben is passionate about fulfilling the site’s mission of making financial advicers better and more successful.
Michael Kitces
Michael Kitces is Head of Planning Strategy at Focus Partners Wealth, which provides an evidence-based approach to private wealth management for near- and current retirees, and Focus Partners Advisor Solutions, a turnkey wealth management services provider supporting thousands of independent financial advisors through the scaling phase of growth.
In addition, he is a co-founder of the XY Planning Network, AdvicePay, fpPathfinder, and New Planner Recruiting, the former Practitioner Editor of the Journal of Financial Planning, the host of the Financial Advisor Success podcast, and the publisher of the popular financial planning industry blog Nerd’s Eye View through his website Kitces.com, dedicated to advancing knowledge in financial planning. In 2010, Michael was recognized with one of the FPA’s “Heart of Financial Planning” awards for his dedication and work in advancing the profession.
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