Private Equity’s next big leap

AI is potentially a game-changer for PE firms seeking advantage in an ocean of data. If widely and responsibly deployed. It can help unlock incredible value previously unobtainable.
“While most companies will be affected by AI, PE firms are likely to be facing the greatest opportunities and risks,” according to Per, “and will also have to be the best and fastest at navigating this disruption.” On one hand, genAI creates a bounty of opportunities for private equity (PE) firms and their assets. It holds the potential to make their deal-making knowledge workers more effective, it can create an additional driver of upside potential for every bid, it can make the integration process more effective, and can offer new levers to improve the performance of their assets before exit.

At the same time, Chris points out, “Harnessing the power of genAI requires technical capabilities that many funds and their portfolio companies lack. It also brings a slew of new operational risks to be managed. Ranging from legal exposure to cyber risks. In addition, genAI raise strategic uncertainties for deal-makers — for example, how to value current assets, how long they should be held, and how much to bid for new.”

This creates an interesting market dynamic. Where some firms are aggressively seeking advantage by being early adopters, others are taking a fast-follower stance to avoid being disrupted — and all are trying to influence their portfolio assets to do the same.

Used appropriately, AI can make humans more productive, by freeing up time spent on tasks that AI tools can do better. It can also accelerate human creativity by re-investing this time to discover new sources of value and competitive advantage. As Chris sets out, “AI won’t replace portfolio managers, but one using AI may eventually replace one who isn’t.”

Per sees at least three major opportunities for PE firms to create value with genAI. The first is to apply it within the fund itself to improve speed and quality of deal process. As Per explains, “when you see that work that previously took days, can now be done in seconds with a simple prompt, you realize how magical this technology can be”. According to the KPMG global tech report, 57 percent of companies believe that AI and machine learning, including generative AI, will be important in helping them achieve their business objectives over the next three years.

The second opportunity is to apply genAI post-close, both during integration and across all portfolio companies during the hold period. As Per says, “If most portfolio companies can use genAI to free up say a third of all knowledge worker hours, this could unlock incremental exit value in the order of several billions of (US) dollars for a medium-sized fund.”

The KPMG global tech report, however, reveals that only 24 percent of PE firms are using AI this widely and effectively. “We’re looking at untapped productivity enhancements across the board,” continues Per, “not just by reducing cost, also by driving more volume with the same cost, selling more effectively and making products more attractive”. We expect this to be the focus for many PE firms in 2024.

Finally, AI may affect what type of assets Pe firms prioritize for investment in the future and how much they are willing to bid. Per explains, “A previously attractive target could rapidly drop in price if now deemed exposed to disruption by competitors leveraging AI. Similarly, an asset with untapped AI potential could attract a bigger bid premium if the buyer is confident both in the diligence and its ability to capture the incremental up-side.”

While AI brings many opportunities, there are costs, risks and barriers to overcome before its potential can be realized. A major obstacle that Chris emphasizes is the foundational role of data to enable high-value use cases, “Moving your data to the cloud is just the entry ticket. Feeding AI models

with high-quality, contextual, indexed, and searchable data is key to unlock full value. This requires a robust data cloud modernization program not yet in place for many PE Firms.”

Another obstacle that Per calls out is the ‘last mile challenge of AI’. This is often overlooked, as Per says, “Even if AI can help knowledge workers free up a third of their time in studies and pilots,

this only translates into real productivity gains if all knowledge workers adopt the tools and re-invest hours saved into something more productive — for example, taking on more volume or higher value-add tasks.”

Per continues, “These are major behavioral changes that cannot be ignored if PE firms are to deliver the productivity gains that AI promises. Success will require a carefully crafted transformation program with a portfolio of actions that hit all behavioral change barriers simultaneously. Solving this, at scale, may be the biggest value creation challenge genAI will face, and not a muscle well trained in prior technology-driven disruptions.”

Lastly, accelerating the use of AI increases risks, like data privacy breaches, more effective cyberattacks and legal challenges arising from intrinsic biases within AI models. This will require a human-in-the-loop for many applications, ‘Trusted AI’ governance frameworks and third-party software. A recent example from KPMG is the spin-out of Cranium in the US, a software platform, offering technology solutions for organizations to adopt and deploy AI models safely. 

KPMG and Microsoft are alliance partners working to enable private equity firms to adapt, transform and innovate. KPMG industry and functional experience, powered by Microsoft technologies, empowers clients to thrive in the era of AI. To find out more about the alliance between KPMG and Microsoft, visit kpmg.com/Microsoft.