Recent market weakness among established data and research firms has drawn private equity scrutiny even as it complicates prospective takeovers. Over the past six months FactSet's stock tumbled 39%, prompting Thoma Bravo and Hellman & Friedman to evaluate potential acquisition scenarios, people familiar with the deliberations said. Morningstar and Gartner have also seen steep declines - down 27.6% and 29.5% respectively since early September - bringing both companies into the crosshairs of investors exploring deals.
That same slide in share prices, however, has become a two-sided consideration for private equity. While lower market values can create apparent buying opportunities, the selloff itself - intensified after a recent upgrade to Anthropic's Claude Cowork AI tool - has raised deep questions about the durability of the business models of software and data vendors. Sources speaking on condition of anonymity because the discussions are private said potential bidders are now reassessing whether they can confidently price acquisitions when the competitive landscape could change rapidly.
Market participants describe the current environment as one in which AI fears are affecting a broad range of companies, from large technology platforms to professional services firms and specialized data providers. Investors worry that advanced AI systems could replicate many of the advice and information products these companies package and sell, reducing demand for proprietary research or diminishing pricing power.
Bankers and buyout professionals say a primary valuation challenge is that company executives cannot reliably forecast how their revenue streams and business models will adapt - or be disrupted - as AI capabilities evolve. That forecasting uncertainty undermines traditional valuation approaches, complicating the underwriting of deals that typically rely on predictable cash-flow projections.
FactSet, Thoma Bravo and Hellman & Friedman declined to comment, and Gartner did not respond to requests for comment. Morningstar did not provide a comment, although CEO Kunal Kapoor told shareholders in a recent letter that he believes the company is "well placed to benefit from the growth of AI." The path to any transaction remains uncertain and dependent on clearer signals about how AI will integrate with or compete against existing enterprise products.
Market perspective
"Public market investors are trying to figure out where the world goes," said Jordan Jacobs, co-founder of Radical Ventures. He emphasized the difficulty of forecasting the next several years in an era where AI is producing rapid improvements and opening up new, fast-moving application areas. That uncertainty has shifted investor preferences: software and data companies that once traded at valuation premiums are now being priced with an "AI discount."
These firms historically attracted high valuations because of their subscription-based, recurring revenue models and strong margins. But those hallmarks are being re-examined. FactSet's enterprise-value-to-EBITDA ratio - a common measure of market value relative to operating earnings - is near 12 today, down from 21 last August and about 30 in 2022, according to LSEG data cited by market participants. Morningstar and Gartner currently trade at ratios of about 12.6 and 14.8, versus roughly 20 and 23 a year earlier.
Operationally, FactSet reported modest growth in its most recent quarter ended November 30: revenue rose 6.9% year-over-year and annual subscription value increased 5.9% year-over-year. However, market observers note that much of that uplift came from price increases on existing subscriptions rather than robust new-client growth. Such dynamics produce steady cash flows but constrain upside potential in a leveraged-buyout scenario.
Cash generation versus growth expectations
For some private equity investors, a mature, cash-generative profile can still be attractive if the buyer prioritizes long-term yield over high-growth upside. Yet this approach depends on confidence that AI will not meaningfully erode pricing power or commoditize the services being monetized. The companies' reduced enterprise values reflect that concern: FactSet's market capitalization sits at just over $8.4 billion, down from $17.5 billion a year ago, according to the figures referenced by market sources.
"Even if you grow 25%, the software business, you won't get the same valuation you get for a pure disruptive AI, which has a $600 billion market opportunity ahead of it," said Shlomo Dovrat, co-founder of Viola Ventures and a board member at Lightricks. His comment underlines a prevailing market distinction between businesses perceived as AI-enabled platforms with massive addressable markets and those viewed as more incremental or defensive subscription services.
Executives and bankers say the market is increasingly differentiating between software deeply embedded within business processes - which may be more resilient - and task-focused tools that could be more vulnerable to AI substitution. That segmentation will likely shape which assets private equity decides to pursue and how they price those deals.
Signs of strategic adaptation
Some vendors are attempting to position themselves as partners to AI developers rather than potential victims of displacement. FactSet's stock rose about 6% after Anthropic named the company as a partner on February 24 to develop new technology tools, an outcome market participants said provided some validation for the thesis that AI developers might collaborate with existing enterprise software firms.
"As the software market bifurcates, some models will be existentially threatened but, more so, there will be great opportunities," said Alex Baker, a partner at PwC and lead of its technology, media and telecom practice. He added that businesses in defensible positions with stable revenue streams could leverage AI as an accelerant and meaningfully outperform peers.
Still, bankers and potential acquirers face a practical problem: accurately valuing firms whose future product roadmaps and competitive moats are being reassessed in real time. Until those uncertainties clear, private equity interest may be matched by equal amounts of caution, with many buyers reluctant to commit to high leverage or aggressive purchase prices.
Summary
Rapid improvements in AI and a related market selloff have made established financial-data and research firms both more affordable and more uncertain as acquisition targets. Private equity suitors are weighing the cash-flow appeal of subscription models against the risk that AI could undercut pricing and product differentiation, complicating valuation and deal execution.