Unlocking AI’s true potential in private equity value creation

By Niko Herborg, Philipp Leutiger and Björn Schubert

Private equity is at a crucial turning point. Traditional value drivers - such as financial engineering and multiple arbitrage - are no longer sufficient to generate returns in a landscape shaped by more extended holding periods, higher costs of capital, and more rigorous buyer scrutiny.

A new mandate for operating partners

Operating partners are taking on expanded roles, expected to cut costs and build resilient, technology-driven, and scalable operations. AI is quickly becoming one of the most powerful tools in that effort - but only if it’s applied with proper business context, speed, and accuracy.

From potential to payoff: Closing the AI gap

Although there is widespread interest, most private equity firms are still in the early stages of AI adoption. Why? The challenge isn’t the technology - it’s the lack of practical implementation. Without the right use cases, clean data, and seamless operational integration, even the most advanced models fail to deliver value.

At Roland Berger, we bridge this gap by directly connecting AI deployments to value creation drivers. Our initiatives are tailored to each portfolio company’s financial objectives, aligned with the investment thesis, and designed to support a compelling equity story at exit.

What we bring to the table: Proven, pragmatic, exit-focused

• A curated library of AI use cases focused on high-ROI areas such as pricing, procurement, engineering, and logistics.
• Use-case-driven AI sprints that deliver results in 4–6 weeks.
• A proprietary AI procurement assistant that flags supplier risks and identifies cost-saving opportunities.
• Cross-functional implementation across operations, finance, and IT to promote business-led adoption.
• Exit-readiness embedded - initiatives are documented to support buyer diligence and enhance valuation.

Examples in action

AI plays a crucial role in value creation programs. These aren’t just theoretical capabilities - they provide measurable benefits for our clients.

• Procurement: AI-driven price benchmarking and category optimization helped a portfolio company save 7% across indirect spend in less than 10 weeks.
• Pricing: In one case, a dynamic pricing model generated an extra $5M in margin within a single quarter.
• Predictive maintenance: An industrial mid-cap asset used AI to cut unplanned downtime by 18%, reducing OpEx and increasing equipment availability.
• Forecasting: AI models decreased forecast errors by 25% while speeding up planning cycles.
• Logistics: Route optimization and inventory balancing lowered working capital needs and improved on-time delivery performance.

Why it matters to PE firms

Private equity firms are increasingly seeing AI not just as a technology investment but as a means to create real value. As buyers seek verifiable, data-backed improvements, firms that can demonstrate how AI has increased EBITDA and lowered operational risks will have a competitive advantage. AI can enhance acquisition strategies, strengthen sell-side narratives, and open up new opportunities for value creation throughout the deal process - from due diligence to exit.

Let’s build it together

AI doesn’t need to be a moonshot. With the proper use case, clean data, and a focused delivery model, it can generate meaningful ROI in weeks - not years. Roland Berger is ready to work with your team to scope, pilot, and expand AI initiatives that add enterprise value and enhance your equity story.

Let’s discuss how to turn AI into EBITDA - and build lasting value.

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