The narrative around artificial intelligence in private equity is undergoing a remarkable shift. After years of AI being primarily deployed as a tool for operational efficiencies and headcount reduction, leading firms are now recalibrating their approach for 2025 and beyond. This strategic evolution reflects a maturing understanding of AI’s potential to drive growth rather than simply trim expenses.
According to a recent McKinsey Global Institute report, private equity firms that leverage AI for revenue enhancement rather than cost reduction are seeing 23% higher returns on their portfolio investments. This data point alone has sparked significant interest across the industry, pushing firms to reconsider their AI deployment strategies.
“We’re witnessing a fundamental rethinking of AI’s role in the private equity playbook,” explains Morgan Stanley’s head of private equity analytics, Sarah Chen. “The first wave was about automation and efficiency. The next wave is about creating new revenue streams and enhancing existing ones.”
This shift comes at a critical juncture. Following the 2022-2023 tech sector correction, many private equity firms found themselves holding technology-heavy portfolios facing valuation pressures. The initial reaction was predictable: deploy AI to cut costs and preserve margins. However, forward-thinking firms quickly recognized the limitations of this approach.
Tide Rock Holdings, a middle-market private equity firm managing over $2 billion in assets, exemplifies this strategic pivot. CEO Ryan Peddycord recently shared at the Financial Times Private Capital Forum that their 2025 strategy explicitly moves away from AI-driven cost reduction.
“We initially saw AI as a way to streamline operations across our portfolio companies,” Peddycord noted. “But we’ve completely reoriented our approach. Today, we’re investing in AI capabilities that create entirely new product offerings and enhance customer experiences.”
Federal Reserve data indicates this shift isn’t merely philosophical. Private equity investments in AI technologies focused on customer acquisition and product development increased 47% in the past year, while investments in automation-focused AI remained relatively flat.
The implications extend beyond individual firm strategies. The broader private equity landscape is adapting to what BlackRock has termed “the second phase of AI integration.” This phase prioritizes revenue enhancement and competitive differentiation over operational efficiency.
A striking example comes from healthcare-focused Riverside Partners, which recently completed a $450 million fundraise specifically targeting portfolio companies capable of leveraging AI for market expansion. Managing Partner David Belluck was explicit: “We’re not interested in using AI to simply reduce headcount. That’s yesterday’s strategy. We’re backing companies that can use these technologies to address unmet needs and expand addressable markets.”
The economic rationale behind this shift is compelling. Boston Consulting Group analysis reveals that while cost-cutting AI implementations typically deliver one-time margin improvements of 8-12%, revenue-enhancing AI applications can drive sustained annual growth rates of 15-20% for properly positioned companies.
This doesn’t mean operational efficiencies are being abandoned entirely. Rather, leading firms are adopting what Bain & Company calls a “dual-track approach” — using established AI tools to maintain operational discipline while simultaneously investing in more innovative applications that drive top-line growth.
TPG’s Tech Adjacencies fund provides an instructive case study. After initially deploying machine learning algorithms to streamline back-office functions across their portfolio, they’ve shifted approximately 70% of their AI investments toward customer-facing applications. These include predictive analytics for personalized marketing, AI-enhanced product development, and intelligent pricing models.
“The returns profile is simply more attractive,” explains TPG’s Chief Technology Officer Katherine Dease. “Cost-cutting has natural limits. Growth-oriented AI applications can compound over time, especially when they create network effects or data advantages.”
The geographic dimensions of this trend are notable as well. While North American private equity firms led the first wave of AI adoption focused on operational efficiency, European firms appear to be leapfrogging directly to growth-oriented applications, according to data from PitchBook.
For portfolio companies, this shift has profound implications. Rather than viewing AI implementation as a threat to headcount, they’re increasingly seeing it as a tool for expansion and competitive differentiation. A survey by Ernst & Young found that 78% of private equity-backed company CEOs now view AI strategy as central to their growth plans, up from just 31% two years ago.
The skills required to execute these strategies are evolving as well. Private equity firms are increasingly recruiting executives with backgrounds in product development and digital transformation rather than cost-cutting specialists. Compensation packages for portfolio company leaders are being restructured to reward revenue growth rather than margin improvement alone.
As we look toward 2025, the indicators suggest this trend will accelerate. Venture capital investments in AI startups focused on revenue enhancement have reached record levels, creating a pipeline of acquisition targets for private equity firms seeking to bolster their portfolios with growth-oriented AI capabilities.
The transformation underway represents a significant maturation in how private equity views technology investments. Rather than treating AI as simply another tool for financial engineering, leading firms are recognizing its potential as a central driver of value creation.
For investors, limited partners, and portfolio companies alike, this shift signals an important evolution in private equity’s approach to technology—one that prioritizes sustainable growth over short-term efficiency gains and positions the industry for a new era of value creation through intelligent applications of artificial intelligence.
