Private equity firms are grappling with a new and persistent headache: artificial intelligence. At the Milken Global Conference this week, industry leaders told Axios that AI has introduced massive modeling challenges for almost any new deal, regardless of sector.
The problem extends beyond backward-looking portfolio losses that can be managed with markdowns or debt renegotiations. Private equity operates on long-term horizons, typically holding companies for at least three or four years. Yet it has been only three-and-a-half years since ChatGPT's launch, and subsequent AI advances—including Claude and Gemini—have continuously reshaped entire industries.
“Modeling exit multiples has always involved a lot of guesswork, but now it feels like throwing at a dartboard blindfolded,” one private equity veteran said. Even firms that partner with major frontier labs cannot claim high confidence in the environment three-and-a-half years from now, according to conference attendees.
The implications are profound for dealmaking. Known unknowns are now more pronounced in every sector, making it harder to price assets, forecast revenue, or predict competitive dynamics. Some sponsors may delay investments until uncertainty clears, while others may demand higher risk premiums.
Critics argue that private equity has long relied on optimistic projections and that AI anxiety may be overstated. They note that modeling challenges are cyclical and that firms have historically adapted to technological disruption, suggesting current hand-wringing could be temporary.