Private equity firms scale AI by adopting a platform-first strategy that moves beyond isolated pilots to a unified infrastructure across all portfolio companies. This approach bridges the "AI Value Gap" by standardising data access, fostering AI literacy amongst leadership, and focusing on measurable EBITDA impacts like operational efficiency and accelerated revenue growth.

Beyond the Pilot: Scaling AI to Boost Private Equity Portfolio Value

In the boardroom discussions of 2024, Artificial Intelligence was the "pilot project" of choice. However, as we move through 2025, the novelty of GenAI has been replaced by a more pressing demand from Limited Partners: measurable value. For Private Equity sponsors, the challenge is no longer about accessing AI models; it is about bridging the "AI Value Gap"—the distance between a successful experiment in one portfolio company and a scalable, EBITDA-driving engine across the entire fund.

The AI Value Gap: Why Pilots Stall

Many PE firms find themselves in a cycle of "random acts of AI." One portfolio company might be using AI for customer service, while another experiments with automated coding, yet neither moves the needle on the fund's overall valuation. This fragmentation occurs because firms lack a unified deployment strategy. Without a standardised approach, every pilot requires a new security review, a new data pipeline, and a new set of skills, leading to "pilot fatigue" and diminishing returns.

The Platform-First Strategy

To drive sustainable growth, forward-thinking sponsors are moving toward a platform-first strategy. Rather than treating AI as a series of bespoke software installs, they are implementing centralised "Knowledge Platforms"—such as Glean—that can be deployed across the portfolio.

A platform-first approach provides the underlying "connective tissue" for a company’s data. When an Operating Partner can deploy a single, secure AI search and synthesis tool across ten different companies, the time-to-value drops from months to days. This consistency allows for central oversight while giving individual CEOs the tools to innovate within their own niche.

Focusing on EBITDA-First AI

In the current market, AI should not be a line item for "innovation"; it must be a lever for efficiency. PE sponsors are prioritising initiatives that directly impact the bottom line:

1. Accelerated Due Diligence: Using AI to synthesise vast data rooms, identifying risks and synergies in hours rather than weeks.

2. Operational Efficiency: Automating repetitive middle-office tasks to lean out the cost base.

3. Revenue Growth: Enhancing sales teams with real-time customer insights and predictive churn models.

Cultivating the Human Element

Technology is only half of the equation. The most successful portfolio companies in 2025 are those where the leadership has high AI Literacy. This doesn't mean every CEO needs to be a data scientist; it means they must understand how AI changes their business model. By fostering a culture of "Warm Intelligence"—where AI augments human expertise rather than replacing it—firms ensure higher adoption rates and more creative applications of the technology.