AI Is Driving Measurable Business Value Across Private Markets

AI has become part of the operational fabric of private markets, driving real business and revenue outcomes. This shift was evident at the 2025 Private Markets AI Summit hosted by The Private Markets Forum. Chaired by Alkymi CEO and Founder Harald Collet, the panel “How AI Achieves Real Business Outcomes” brought together industry leaders to discuss how firms are building measurable, scalable value with AI today.

The conversation tackled one of the most pressing challenges in the industry: how to make AI actually deliver. Panelists explored how to structure and scale smart pilots, build business cases that stand up to scrutiny, and integrate AI into workflows that generate both revenue and operational efficiencies. They also shared practical examples from their own organizations across research, compliance, and due diligence, offering a blueprint for moving from pilot to production.

Panelists included:

• Sonja Renander, Managing Director, U.S. Credit, Oak Hill Advisors
• Sanjesh Dubey, Senior Manager, Technology Consulting, Ernst & Young LLP
• Steve Siler, Chief Technology Officer, North Mill Equipment Finance

From Pilots to Production: What’s Actually Working

The panel explored what is actually working in AI today. Each panelist shared real-world frameworks that helped move AI projects from theory to production. While early-stage experiments remain valuable, the consensus was that true impact comes from operationalizing AI across repeatable workflows rather than running isolated pilots. The firms seeing success have built structured approaches to data readiness, process alignment, and performance measurement, allowing them to transform smart pilots into sustainable business practices.

Quantifying ROI: The New Language of AI Value

A recurring theme was the need for clear ROI. Rather than chasing abstract innovation, private markets firms are prioritizing projects that show measurable business outcomes, whether through efficiency gains, cost savings, or new revenue streams.

Panelists discussed the balance between front-office innovation and back-office automation, noting that both deliver tangible value when integrated into broader data strategies. As one panelist noted, “The firms seeing the most success are the ones that treat AI not as a separate initiative, but as a natural extension of workflow optimization.”

Overcoming the Challenges: Data, Adoption, and Regulation

AI adoption is not without challenges. The group explored the roadblocks that slow transformation, including fragmented data, security constraints, regulatory uncertainty, and the complexity of cloud migration. Many firms are still working to make data accessible to AI systems while maintaining control and compliance.
The takeaway was clear: success requires equal investment in data strategy and change management. Technology alone is not enough. People, processes, and governance need to evolve in parallel.

What’s Next: Building a Roadmap for Real Outcomes

As the session wrapped up, the audience was encouraged to focus on actionable step:

• Identify one workflow where AI can deliver measurable business value.
• Audit data readiness and define ownership boundaries.
• Align stakeholders across front- and back-office functions to avoid siloed initiatives.

AI will only move the needle for private markets when it becomes part of the operational fabric. The opportunity lies in scaling real, repeatable outcomes, not chasing the next big model.

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