Private equity companies are deploying AI experts to identify inefficiencies and additional revenue opportunities. 

Tech experts are tasked with learning to “leverage AI to hunt for hidden profits in operations or accelerate profits within [a PE firm’s] portfolio,” Molly Buxton, principal at data analytics company JMAN, told FinAi News. 

PE companies are looking to use AI to boost their bottom lines, Buxton said, adding that JMAN, which primarily works with private equity firms, is using AI both in its own operations and deploying it in the PE firms in its portfolio.

“There are still a lot of highly manual processes across organizations that PE invests in,” Buxton said. For example, PEs can deploy AI teams to make one of their manufacturing portfolio company’s operations more efficient by automating the accounts receivable process or make the raw material acquisition process simpler. 

Pre-acquisition and post-acquisition uses 

Charles Corpening, chief investment officer at PE firm West Lane Partners, told FinAi News that primary uses for AI within PE operations are:  

• Sourcing deals; 
• Valuation and benchmarks; and
• Accelerating due diligence. 

West Lane Partners sees AI as a way to source opportunities, Corpening said.  

“It can flag companies that are expanding hiring, changing their digital footprint, or showing signs of breakout growth before they hit the radar of intermediaries,” he said. 

The Morristown, N.J.-based West Lane is also deploying AI as an additional layer of diligence, “particularly for broadly scanning news, court filings and social media for red flags,” Corpening said. 

“We see as much potential for AI post-acquisition as pre-acquisition,” Corpening said. “Once a private equity firm has acquired a business, AI can help identify efficiencies in pricing, supply chain or customer churn that wouldn’t necessarily show up in a standard 100-day plan.” 

West Lane declined to quantify its efficiency gains from AI. 

However, Balika Sonthalia, senior partner and practice lead of Americas in the strategic operations practice at consulting company Kearney, told FinAi News that PE firms using AI see productivity gains in the 10% to 40% range for structured analytical and drafting tasks. 

“We are not yet seeing public data showing direct impact on fund-level returns, but we are seeing meaningful acceleration in diligence and reporting processes,” she said. 

PE and technology 

Private equity firms are generally not building their own AI technology, Sonthalia said. 

“They are developing tech capabilities in three ways:  

• Partnerships;  

• buying; and 

•  selectively building in-house teams of data scientists, AI product managers, digital operating partners,” she said. 

These tech teams may fine-tune models or build lightweight internal copilots, but they rarely develop proprietary large language models, Sonthalia said.  

“Some larger funds have strategic partnerships with technology firms to build repeatable playbooks for portfolio AI deployment,” she said. 

The dominant model today for PE funds is still to partner with established AI vendors or using enterprise-grade platforms with strong data governance controls, Sonthalia said.  

“Larger firms, particularly those with centralized operating teams, may acquire analytics or AI-focused service firms to strengthen portfolio support capabilities,” she said. 

Register here for the inaugural FinAi Banking Summit, taking place March 2-3 in Denver. View the full event agenda here.