The Convergence of AI and Private Equity

Introduction

There’s not a tech headline these days that doesn’t mention artificial intelligence or that jobs are in danger of being replaced by robots layered with AI.  The current AI boom is reminiscent of the late ’90s internet craze, you almost can’t go anywhere without bumping into the founder of an AI startup.  Much of it can be somewhat overwhelming at times; however, when business figures such as Elon Musk, Sundar Pichai, Larry Ellison, Robert Smith and Steve Schwarzman are pouring astounding amounts of money into AI, perhaps it’s wise to lean in a little over the next 10 years.

AI and Private Equity

The investment and private equity industry is not immune to the AI wave and stands to benefit from it immensely.  The proposed strategy is to embrace the new technology and utilize it to increase efficiencies, as opposed to avoiding it; avoiding internet business models didn’t work out too well for the record and newspaper industries in the 2000s.  Like many, myself and my colleagues have been tracking the AI industry both from an operational, as well as portfolio company perspective.  The following is recent, notable content with respect to the convergence of the AI and private equity industries, as well as quick takeaway points both from the resources below and our own comments that may provide food for thought whether you’re running an investment firm or a product or service company.

Insightful Content

Bain & Co. - Field Notes from the Generative AI Insurgency in Private Equity, by Gene Rapoport et al., March 3, 2025  https://www.bain.com/insights/field-notes-from-generative-ai-insurgency-global-private-equity-report-2025/

Bond Capital – Trends in Artificial Intelligence, by Mary Meeker et al., May 30, 2025….340 slides and all worth it if you are familiar with her content https://www.bondcap.com/reports/tai

Harvard Business Review – How Private Equity Firms are Creating Value with AI, by Vikram Mahidar et al, June 16, 2025  https://hbr.org/2025/06/how-private-equity-firms-are-creating-value-with-ai

Quick Takeaways and Notes on the Convergence of AI and Private Equity

• When and where do you utilize AI in PE?

- Firm operation itself

- Identification of targets and due diligence

- Transaction execution (whether acquisition or sale)

- Use of AI to improve operations in portfolio companies

• How to utilize AI?

- Individual employee productivity (email, calendaring, slide decks, financial modeling)

- Target outreach

- Research and data insights (broadly and in many contexts)

- Product development (create and design)

- Product reiteration and improvement

- Software development (code or otherwise); this is particularly important in software portfolio companies to increase efficiency and reduce expense

- Financial and legal document production (at least initially)

- Virtual sales assistants and communication

- AI assisted cybersecurity across the operation

• Opinions of AI in PE vary significantly with some of the following:

- Why would I allocate investing funds into a PE portfolio company for an expensive AI and data platform for a company I’m going to flip perhaps quicker than the AI investment will payoff?

- We’re investing heavily into AI at both the firm and portfolio company level, immediately (particularly with the larger funds who have the vision and dollars to do so).

- The jury is still out, “but we’re looking into it”……you hear this a lot in PE and investment banking circles, but there’s some truth to it, it’s very hard to find any actual financial data yet for ROI resulting from AI utilization other than projections.

• Implementation of AI poses interesting issues, problems and opportunities in the PE industry - who will develop and implement such AI utilization for a PE fund and/or its portfolio companies (this can apply to a product company as well)?

- Should the AI implementation and management be done by an external firm/agency?

- Should the PE fund have its own in-house AI/data/software team for the firm and its portfolio companies?  In this case, it’s easier to share insights across the platform/portfolio

- Should each of the portfolio companies have their own respective AI teams?

• Over 50% of PE portfolio companies are using generative AI in some capacity and 20% have operationalized generative AI.

• Are PE firms and portfolio companies working together on their AI initiatives or is the portfolio company simply working alone?

• Are portfolio management teams hesitant or stubborn to use AI?

• Are portfolio companies considering using AI to address their most significant business issues or only for individual productivity tasks?

• Does the PE firm and/or each portfolio company have an actual AI strategy?

• Target company valuations become more difficult in the current AI boom.

- Is the target optimized for AI and data capability?

- What’s the value of a company that doesn’t use AI?

- What’s the value of a company that does use AI?

- What impact is AI going to have on the target’s industry?  What is the risk profile?

- Does the company have its own data to train AI models?

As you can see, there’s a lot to consider in implementing artificial intelligence into a private equity operation and/or one of its portfolio companies, the above thoughts or insights may be helpful.  Artificial intelligence can and will be able to do a lot of things, but very generally and in a variety of instances, it allows a professional or company to procure or create information in a more efficient manner; then typically provides deeper (or at least additional) insights related to such information; and depending on the AI software application being used, automate certain items - this could be drafting an email, designing a new product, identifying where a Fortune 100 company is most inefficient or unprofitable in its organization or automating almost your entire sales team while maintaining certain leadership. 

We’re in about the second or third year of any sort of meaningful AI usage by the commercial public.  I would equate that to the top half of the first inning of a baseball game, or in internet industry terms, we’re in about year 1996, and now we’re roughly 30 years later.  From a media perspective, there’s a lot of hype around AI, but at the same time, it’s definitely already proven to be a disruptive and productive technology, and if utilized, will assist significantly in private company investments from research to automation.