AI is rapidly changing how private equity managers do deals. It is determining which firms will be most competitive, altering the day-to-day jobs of junior staffers and freeing up time for all employees to do more meaningful work.
But some firms find the juice is not always worth the squeeze.
Many GPs are embracing the technology to support their work across the investment cycle, from scouring data rooms in due diligence to leveraging financial data and meeting notes to identify acquisition targets. AI can also streamline fund formation and simplify legal work in fundraising.
Early adopters praise the technology, won over by its prowess and the head start it gives them over rivals. They recognize its value in freeing up labor for new challenges.
“Firms that do not invest in these capabilities might find themselves disintermediated by those using it to their advantage, either to make better investment decisions or to be a better value-added partner to their portfolio companies,” said Tim Osnabrug, an investment partner with Investcorp’s Strategic Capital Group (ISCG).
“Whatever it is, you gotta get involved now,” he added.
ISCG, which buys minority stakes in private asset managers, uses a generative AI-powered platform made by DiligentIQ to streamline its due diligence process.
The software, from a company founded by former KKR CIO Ed Brandman, handles a variety of tasks that typically require extensive manual labor.
Osnabrug told me that the software helps his team save up to 80% of the time it would generally spend on due diligence, which can consume thousands of hours and thousands of dollars in legal fees per transaction.
“We feel that middle-market GPs in our portfolio, [and] almost every business, [have] to bring and make AI as part of the conversation. Otherwise, there’s a real potential that they’re going to miss out and be put into a less competitive situation,” said Ravi Thakur, the COO & GP Development Partner at ISCG.
Despite the growing interest, AI has yet to gain traction across the PE market.
Some say that the lower end of the market—defined as GPs managing less than $1 billion in assets—has been slow to adopt it.
Larger funds stand to gain more from tools designed for sourcing and due diligence as they can draw on bigger datasets for insights, said Taylor Lowe, the CEO and co-founder of Metal, which offers an AI-powered platform to help PE firms with due diligence and the investment process.
Established firms with decades of history have vast archives of investment memos, deal records and conversations that AI can use to build a database and help identify targets that match an investment thesis, Lowe said.
Smaller firms and emerging managers can lack that extensive information, and if they have the data, it tends to be more fragmented and not written down, making a specialized AI platform less useful.
“It’s just a byproduct of how the larger funds typically work,” Lowe said. “But if you’re a document-heavy smaller fund, you may also have access to that data.”
Additionally, larger firms may have more resources to invest in new technology. “If you have a bigger AUM and more resources internally, you’re able to build use cases and tools across the areas that you need the most,” said Howard Gutman, a senior manager at MorganFranklin Consulting.
Others, though, argue that it is not the size of the firm but skepticism about the technology that has held some back.
Osnabrug said he has seen multi-billion-dollar GPs resist the use of AI, while some specialist managers with around $1 billion in assets move ahead of the curve, integrating AI into investment processes.
With less bureaucracy to navigate, middle-market firms can often adopt new technology quickly, and many are more willing to experiment with innovation.
“Bigger doesn’t necessarily mean faster and more innovative, and you can draw the parallel to large global technology companies,” Osnabrug said.
Adopting the new technology does come with a learning curve, which requires tolerance for inefficiency early on.
“We can see sometimes people are very excited in the beginning until they hit roadblocks and revert to old habits, and then it kind of dies out,” Osnabrug said.
Finally, while AI makes dealmaking more efficient, it also raises fears about job security, particularly among lower-level professionals. Some specialized AI systems have become affordable. Metal, according to Lowe, prices its software at a starting price of $24,000 per year.
Osnabrug argued that using AI improves efficiency across his team and frees everyone from repetitive tasks. Junior professionals can spend more time analyzing investments, assessing risks and identifying value-creation opportunities, while senior staff can devote more time to finding opportunities and meeting with management teams at target businesses.
“It improves the enjoyment that our team members have from the work,” Osnabrug said.
Featured image by Chloe Ladwig/PitchBook News
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