How Private Equity Firms Are Applying AI: Insights from the 2026 Private Equity CFO Conference.

Citizens Private Bank recently hosted the 2026 Private Equity CFO Conference at the Hotel del Coronado in San Diego. Bringing together private equity finance leaders, operators, advisors and industry specialists, the conference is designed to facilitate the exchange of practical insights that participants can apply within their own organizations. This year, many of the discussions involved artificial intelligence, with experts sharing perspectives on how firms are evaluating the technology, identifying use cases and beginning to incorporate AI into day-to-day operations.

The conversations reflected an industry that is still early in the AI adoption cycle, but discovering quickly what role AI can play. Below are several of the key insights that emerged from those sessions.

Where private equity firms are seeing early AI results

A range of practical AI applications are already being tested across private equity firms. Firms are beginning to leverage AI in the investment and operational workflows:

• Research support and information gathering. Teams are using AI to summarize materials, synthesize information from multiple sources and accelerate preliminary research tasks.
• Meeting preparation. Participants discussed using AI to prepare briefing materials, organize background information and streamline meeting preparation workflows.
• Internal reporting. Firms are exploring ways to automate portions of recurring reporting processes and reduce the time required to compile internal updates and management information.
• Administrative workflows. Many early use cases focus on reducing manual work associated with routine operational tasks, allowing teams to devote more time to higher-value activities.

Discussions also extended beyond knowledge work and into finance and fund operations, where firms are evaluating how AI may support highly structured processes:

• Finance and accounting applications. Firms are finding opportunities to use AI for fund administration, reporting, reconciliation processes and other finance functions that rely heavily on structured data.
• Fund operations and investor reporting. Demonstrations showed how AI can assist with reviewing fund documents, interpreting subscription materials, supporting capital call calculations, generating investor notices and preparing supporting documentation for fund operations.
• Portfolio monitoring and data collection. Some firms are evaluating how AI may help collect, organize and analyze information across portfolio companies, creating more consistent reporting and greater visibility into operating performance.
• Knowledge management and document retrieval. Several attendees discussed connecting AI tools to internal repositories and data environments, allowing employees to locate information more efficiently while maintaining appropriate permissions and access controls.

Rather than attempting to reengineer investment processes immediately, many firms appear to be starting with workflows where efficiency gains can be measured, implementation risk is manageable and results can be evaluated quickly.

How AI can support portfolio company value creation

One open question that many firms are working through is how AI will create value across portfolio companies. Participants described a growing interest in using AI to support operational initiatives, improve visibility across businesses and help management teams work more effectively with existing information.

Specific areas of exploration included:

• Researching operational improvement opportunities. Teams are using AI to gather information, summarize findings and accelerate preliminary analysis around business challenges and potential initiatives.
• Identifying patterns across portfolio businesses. Firms are exploring how AI may help compare information across multiple companies, making it easier to spot common challenges and recurring themes.
• Portfolio monitoring and reporting. Discussions referenced opportunities to organize and review information from portfolio companies more consistently, helping investment and operating teams maintain visibility across the portfolio.

Several attendees also discussed the potential for AI to help capture institutional knowledge and share successful practices across portfolio companies. As a result, many firms view portfolio-level initiatives as a practical environment for testing AI applications while generating measurable business outcomes.

Building safe environments for AI experimentation

An unusual aspect of AI's adoption, compared to other new technologies, is a preference to learn through experimentation rather than pursue large-scale transformation initiatives. Instead of deploying AI broadly across the organization, many participants described efforts to test specific use cases, measure outcomes and expand adoption as confidence grows.

One practical framework discussed during the sessions was to start with a specific operational challenge, identify a platform capable of addressing it and designate an internal champion responsible for testing and evaluation.

Deployment practices included:

• Starting with contained use cases. Many firms are focusing initial experimentation on research, reporting, administrative workflows and other processes where results can be evaluated without affecting core investment decisions.
• Establishing clear ownership. Successful implementations were frequently associated with individuals or teams responsible for driving adoption, evaluating outputs and sharing lessons learned across the organization.
• Evaluating outcomes before scaling. Participants emphasized the importance of determining whether a use case is actually improving efficiency or producing a better result before wider deployment.

Participants noted that experimentation increasingly requires governance to develop alongside innovation. Governance should be visible and outline policies regarding unauthorized "shadow AI" usage, prompt injection risks and practical guardrails that allow employees to explore new tools while maintaining appropriate security and oversight. Firms also discussed updating policies regularly as new capabilities and use cases emerge.

Data stewardship and institutional knowledge

Several panelists noted that the value of AI is often constrained by the quality and accessibility of underlying information. Firms with well-documented processes, consistent reporting standards and organized data repositories may be better positioned to apply AI across functions.

Participants also discussed the challenge of capturing expertise that often resides with individual employees or partners. As firms evaluate AI capabilities, many are simultaneously examining how knowledge is documented.

AI readiness increasingly appears connected to broader efforts around data stewardship, documentation and institutional knowledge management. Those foundational capabilities may help determine which future AI applications a firm can realistically support.

How AI adoption strategies differ across private equity firms

Even though many of the benefits and challenges of AI adoption appear to be universal, firms are approaching AI adoption in their own unique ways. Strategies vary based on firm size, resources, operating models, risk tolerance and the maturity of existing technology infrastructure. Some firms are moving aggressively into new use cases, while others are taking a more measured approach focused on governance, data readiness and controlled experimentation.

Despite those differences, many attendees appeared to be working through similar questions around workflow integration, institutional knowledge, measuring value from early deployments and identifying where AI can produce meaningful business outcomes. The industry remains early in the adoption cycle, but the focus has shifted from theoretical possibilities to practical applications.

Through events such as the Citizens Private Bank CFO Conference, Citizens Private Bank engages with private equity leaders on the operational, financial and strategic issues affecting the industry. As firms continue to evaluate how AI may affect investment processes, portfolio companies and day-to-day operations, sharing experiences and practical lessons can help inform implementation decisions. To learn more about the topics discussed at the conference and how they may apply to your organization, contact your Citizens Private Bank relationship manager.

For additional insights from the conference, read our 2026 Citizens Private Equity CFO Conference recap.