Egon Zehnder Examines the Great AI Divide Reshaping Private Equity Leadership

October 21, 2026 – Private equity firms are moving quickly to determine where AI can create the greatest advantage across portfolio operations and investment strategy. As adoption accelerates, firms are rethinking what kind of AI leadership they need and where those roles should sit. That shift is beginning to reshape talent strategies across the PE market. Over the past couple of years, private equity firms have moved quickly to onboard AI leadership capabilities, according to a recent report from Egon Zehnder’s Anna Auerbach, Brian David, and Christoph Wollersheim.

What began as a question of AI strategy has become a more practical challenge: determining what kind of AI leader the firm actually needs. At first, the solution may seem simple: bring in an AI operating partner, name a head of AI, or establish a center of excellence.

“Yet many firms are discovering that AI leadership is not a single, uniform role,” the Egon Zehnder report said. “In practice, they are often trying to solve two distinct problems at once. “Both matter. Both require new leadership. But increasingly, they look like different jobs. And that distinction may shape the next generation of talent in private equity.”

The First Wave: AI as a Value Creation Lever 

This is where most firms started, the Egon Zehnder report explained. “Private equity has always been built around creating enterprise value,” the study said. “AI is now adding to that end. The portfolio-side agenda is relatively clear: How can a company sell more effectively, serve customers better, modernize operations, speed product development, enable sharper decisions, and ultimately improve EBITDA and enterprise value?”

An AI leader operating in this world is fundamentally a value creation executive, the Egon Zehnder report noted. “Their clients are portfolio company CEOs and management teams,” it said. “Their success is measured by tangible business outcomes: revenue growth, cost reduction, faster execution, and higher enterprise value. The economics are therefore relatively easy to understand. The investment is visible. The return is visible. Overall, the value creation story fits neatly within the traditional private equity operating model.”

The Second Wave: AI as an Investment Lever 

Egon Zehnder also explained that the more interesting conversation is now emerging at the fund level. “Increasingly, firms are asking whether the biggest AI opportunity is not only in the portfolio, but in how the firm makes investment decisions,” the report said. “This is where the discussion shifts from value creation to investment performance. The fund-level AI agenda is not primarily about helping companies operate better. It is about helping investors invest better.”

Related: With millionways Investment Hunt Scanlon Ventures Backs the Future of AI-Powered Talent Platforms

“That agenda touches nearly every part of the investment process: deal sourcing, diligence, industry analysis, thesis development, risk identification, knowledge sharing, portfolio monitoring, and investment committee preparation,” the Egon Zehnder report continued. “It also includes the internal transformation of its functions to increase performance and to reduce overhead. That is a very different mandate. The portfolio-side AI leader is trying to create better companies. The fund-side AI leader is trying to create a better investor. One is measured by operating performance. The other is measured by decision quality. One focuses on EBITDA. The other focuses on judgment.”

Why Large Funds Have an Advantage 

The largest alternative asset managers are increasingly treating AI as a platform capability, not a technology initiative, not an isolated operating function, and not a collection of disconnected pilots, according to the Egon Zehnder report. “At scale, the logic is compelling,” the study said. “Large firms can build centralized teams, shared tooling, common governance frameworks, repeatable diligence capabilities, dedicated AI expertise, portfolio-wide playbooks, and knowledge systems that improve with every investment.”

millionways Brings a New Behavioral Intelligence Lever to Executive Recruiters

Hunt Scanlon Ventures has completed its investment in millionways, a New York-headquartered company that builds a behavioral intelligence layer of AI for human agent workforces, utilizing a proprietary Large Psychology Model called Thorsten-4. The platform focuses on understanding human signals, motives, and behavior patterns, with applications used across AI governance, executive hiring, talent management, and enterprise environments.

“millionways is a trailblazer in this newly emerging space,” said Scott A. Scanlon, CEO and co-founder of Hunt Scanlon Ventures and a senior advisor to company co-founders Martin Cordsmeier and Max Weidemann. “As investors, we see behavioral intelligence as a new layer of AI infrastructure, giving artificial intelligence a missing layer – the ability to interpret the human dynamics behind communication and decision-making. In our view, organizations that can better understand the convergence of leadership and human behavior patterns will create meaningful competitive advantage in the years ahead. Behavioral intelligence will become central to everyday enterprise decision-making,” he said.

Mr. Scanlon noted that artificial intelligence is already making big inroads and reshaping the human capital sector. “Organizations have embraced AI to automate workflows, improve performance, and generate insights on people. As those capabilities mature, the next phase is poised to move beyond productivity and efficiency toward improving the quality of human judgement,” he said. “Reducing this friction is an essential next step for businesses in general, but a critical one for the human capital ecosystem.”

The objective is not simply to help one company adopt AI. The objective is to improve the entire investment engine. “In that sense, AI is becoming another institutional capability – much like sector expertise, operating expertise, or capital markets expertise,” the Egon Zehnder report said. “Over time, the firms with the strongest AI operating models may simply become better investors. That is a very different source of advantage.”

Why the Middle Market Faces a Tougher Challenge 

Egon Zehnder also says that the story looks different in the middle market. “Most firms cannot justify building a fully dedicated AI platform overnight,” the firm explained. “They do not have unlimited resources, hundreds of portfolio companies, or large internal AI organizations. And most cannot justify hiring multiple AI executives. Instead, they often want one person to do everything: support portfolio companies, advise CEOs, strengthen diligence, educate investment teams, identify AI opportunities, develop playbooks, evaluate new investments, drive adoption, and shape strategy.”

“The challenge is that these responsibilities often require different capabilities,” Egon Zehnder added. “The operational mindset needed to help a manufacturing company automate processes or a healthcare company redesign workflows is not necessarily the same mindset required to rethink investment committee preparation, sourcing strategy, or diligence processes.”

This raises a practical question that is especially acute for middle-market firms: what employment model should the fund use for AI leadership? “The options can look quite different in practice: an AI-focused operating partner, a chief AI officer for the fund, a chief AI officer embedded in one or several portfolio companies, or a more flexible AI-focused advisor,” the Egon Zehnder report said. “Smaller and mid-market funds may be more likely to start with advisors, using them to test priorities, build conviction, and support targeted portfolio needs without committing to a full-time platform role.”

Related: Beyond the Single AI Path: You Can Have It All 

“Beyond an advisor, there tends to be more of a case for hiring an AI operating partner for the portfolio side, versus a broader CAIO or targeting fund transformation,” the report added. “Larger funds, by contrast, are more likely to build toward a dedicated CAIO, an AI-focused operating partner, or both. Portfolio-company CAIOs may make sense only when technology and AI are central to the value creation plan, rather than as a generic solution across the portfolio.”

The Change Management Problem Nobody Talks About 

There is another reality that is often overlooked: private equity firms are highly effective at driving change inside portfolio companies, according to the Egon Zehnder report. “That is what they do,” the study explained. “But driving change inside the partnership itself can be significantly harder. The irony is that AI adoption may be easier inside some portfolio companies than inside the fund. Portfolio companies often have an obvious business case: the ROI is visible, the mandate is clear, and the urgency is tangible.”

At the GP level, the conversation becomes more complex. Investment professionals have often been enormously successful operating in a particular way. “Their processes have worked,” Egon Zehnder said. “Their judgment has worked. Their pattern recognition has worked. AI challenges some of those habits. It changes how research is conducted, how diligence is performed, how memos are written, how information is synthesized, and how investment decisions are made.”

Egon Zehnder says that those are deeply embedded behaviors. Changing the behaviors of highly successful knowledge workers is rarely easy. While the technology challenge may be solvable, the human part of the equation is often harder. This, of course, is an ongoing challenge for professional companies as well.

The Future Belongs to Translators 

“This is why the most successful AI leaders in private equity may not be pure technologists, and they may not be pure investors either,” the Egon Zehnder report pointed out. “They may be translators, leaders who can move comfortably among portfolio CEOs, operating partners, deal professionals, investment committees, and technology teams. They understand both value creation and investment decision-making. Most importantly, they can tie AI initiatives directly to returns.”

That is the dividing line. “The first generation of AI leaders in private equity was hired to help portfolio companies use AI,” the report said. “The next generation may be hired to help investment firms become AI-enabled organizations themselves. One creates better businesses. The other creates a better investor. Over the next five years, private equity firms will likely discover that the second challenge is the harder, and potentially the more valuable, of the two.”

Egon Zehnder concluded that the firms that solve both will not simply generate more value in their portfolios. They may develop a structural advantage in how they source, evaluate, and support investments. “In an industry where differentiation is increasingly difficult to sustain, that may prove to be one of the most important competitive advantages of the AI era,” the report said.

Related: AI Is Rewriting the Executive Hiring Playbook

Contributed by Scott A. Scanlon, Editor-in-Chief and Dale M. Zupsansky, Executive Editor  – Hunt Scanlon Media