Private equity funds are racing to understand the impact that recent advances in artificial intelligence could have on portfolio companies but have made only tentative progress in using AI software tools to improve their own operations, like the sourcing of new investments.

"That's something funds are thinking about, but there's probably 10 or fewer funds that are really making a big push there," said Richard Lichtenstein, an expert partner at Bain & Co. who leads a team building AI-powered software tools for the firm's private equity clients.

That could soon change if more private equity firms follow the path being blazed by some of world's largest alternative asset managers, including The Carlyle Group Inc. and Blackstone Inc., which have discussed the deployment of AI internally and at portfolio companies on recent earnings calls. Blackstone employs a 50-plus member data science team and is "rapidly and significantly expanding" its AI capabilities, CEO Stephen Schwarzman said on the firm's second-quarter earnings call.

"We believe that the new generation of AI has the potential to transform companies and industries. And the timeliness and effectiveness of its implementation will be determinative of who the winners and losers will be," Schwarzman said.

Potential uses

Lichtenstein, who has consulted with 80 private equity firms on AI, said at least one firm is actively trying to build an AI tool to advise on investment decisions. Such a tool could eventually offer a thumbs up or thumbs down on a particular company and explain its reasoning.

"It's on the near-term horizon, but I wouldn't say we're there yet," Lichtenstein said, estimating that the AI-powered bot may be as little as six to 12 months away.

"And then once you've built the bot, before you're ready to give it a vote on your investment committee, you probably want to experiment with it a lot and test it and see where it's biased and try to correct for those biases," Lichtenstein said.

Another potential use of AI by private equity is for combing through the countless bytes of proprietary data the firms collect from portfolio companies and then combining it with data from sources outside private markets to produce unique insights, said Akash Takyar, CEO of AI software development and consulting firm LeewayHertz Technologies Pvt. Ltd.

"Only AI can make sense of it because these are unstructured data. Some of these are PDFs, some of them are databases, some of them are Excel [spreadsheets]," Takyar said. "A large language model like generative AI is much better at figuring out the context from multiple data sources."

That particular AI use-case scenario is one that also touches on a serious concern for private equity and possibly the greatest impediment to more widespread adoption of the technology: that allowing the software to access private equity firms' proprietary data could erode the firewall they use to keep that data away from competitors.

"The biggest hurdle, they feel, is their risk governance," Takyar said.

First steps

For now, AI deployment within private equity firms is focused on partially automating labor-intensive tasks. Carlyle CEO Harvey Schwartz described AI-enabled operation efficiencies as "an important driver of growth and scale over the long term" on the firm's second-quarter call.

Tasks ripe for AI include contacting prospective investment targets, Takyar said. In his example, an unsolicited or "cold email" is drafted by an AI bot in the form of the private equity firm's introductory letter to a company. It could be personalized with details scraped from public websites like LinkedIn to be more engaging and, if successful, more likely to generate a response.

"This idea specifically came out of a conversation with a private equity firm," Takyar said.

Lichtenstein described another AI tool, one that private equity investors in the consumer sector can use to quickly analyze and characterize online reviews for a particular company and even respond to questions via a chatbot. It is a labor-intensive process that many firms now outsource to specialists, Lichtenstein said.

Focus on portfolio

At the moment, private equity firms are less focused on developing AI tools for their own operations and more on understanding how a burgeoning AI revolution could impact their portfolio, Lichtenstein said.

"The number one issue on the top of all the 80 funds I've talked to is, do I own any companies that are going to have their value significantly impacted by generative AI." Lichtenstein said. "Question number two shortly behind that is, do I have any companies that need to move quickly to take advantage of an opportunity to become much more valuable because of generative AI."

"Many funds are just stopping there. Many funds are saying, 'Find those companies, help them figure this out,'" Lichtenstein said.

A third priority, especially for software-focused funds, is identifying those sectors or subsectors at the greatest risk of disruption by AI and incorporating that knowledge into the due diligence process for new investments, Lichtenstein added.

The swift uptake of AI in the education services sector, for instance, is already inflecting private equity investment in the space, which saw private equity-backed deal values jump 47% year over year in the second quarter.