Below are key highlights from our PE CFO Roundtable in New York City, October 2025

We recently convened a group of PE and VC CFOs to discuss AI adoption in their firms. The conversation revealed a pragmatic, measured approach offering valuable insights into what’s actually working – and what’s still being figured out.

The Basics

Most firms have standardized ChatGPT or Claude as foundational tools, deploying enterprise licenses with appropriate data controls. While compliance teams are understandably cautious about personally identifiable information (PII), these platforms are proving to deliver significant productivity improvements.

We found that using AI to significantly shorten task timelines is quickly becoming standard practice among us. This not only enhances efficiency but also sets a new benchmark for production.

High-Impact Use Cases

Everyone was excited to discuss practical applications that are working right now and generating immediate returns:

Expense management is a clear area for quick wins. Many firms use Concur or Ramp’s AI-enabled platforms, which have effectively eliminated traditional expense reporting. The time previously spent by administrative staff on receipt management and reconciliation has been redirected to higher-value work.

Document analysis is proving valuable across functions. Teams are using AI to synthesize contracts, investment memos, and technical reports in minutes rather than hours.

Transcribing calls and video conferences has emerged as a “killer app” for many users. The ability to capture details from conversations and quickly synthesize information has become invaluable. However, there’s a consensus that not every conversation should be recorded. Currently, most firms rely on judgment, but there’s an opportunity to establish clear controls to ensure that private conversations remain confidential.

Portfolio monitoring and analysis is a rapidly expanding application that stands to benefit greatly from advancements in AI. Firms are significantly enhancing their monitoring efforts by using AI to aggregate key performance indicators (KPIs), benchmark similar deals, extract financial data, and analyze performance across their entire portfolios.

Human review and refinement are still necessary, but AI’s efficiency and effectiveness in organizing and presenting information is undeniable.

The Hidden Cost of AI Tools: Are You Double-Paying for Compute?

Are firms effectively paying twice for the same underlying technology? Many vertical software solutions are essentially wrappers around general-purpose models like ChatGPT or Claude. This means you’re covering your existing enterprise AI license plus the vendor’s compute costs.

Before committing to expensive specialty tools, CFOs should ask: “Can we achieve this with better prompting and creativity using our existing GPT license?” The answer, especially for initial proofs of concept, is often yes.

No More Free Lunches?

Recent tax law changes have made employer-provided meals taxable for employees, prompting firms to reevaluate their lunch offerings. Some companies continue daily lunches as a retention tool, others have switched to a Monday-only model, while some have eliminated the benefit.

The Future of Fund Administration: Disruption is Coming

The most robust discussion centered on fund administrators, as it should, as many firms are dissatisfied with theirs.

The core problems:

  • Data access is the primary frustration. Even firms using quality administrators and co-sourcing models struggle to get access to their own data when and how they want.
  • Legacy technology infrastructure. Firms expect AI technologies to improve delivery, yet, have low expectations that the legacy firms are sophisticated enough to implement them or willing to disrupt themselves.
  • The switching threshold is high. Making a switch is a major undertaking; savings would need to be significant to justify the operational disruption.

The consensus is that significant disruption is coming within 3-5 years, but the endgame is still unclear.

Path 1: Legacy providers with strong service records invest heavily to tech-enable their platforms, offering real-time data access while maintaining their reliability advantage.

Path 2: Tech-first platforms (like Juniper Square or Carta) mature their operations to the point where they offer reliability comparable to that of traditional providers.

The wild card: AI enabling firms to bring more work in-house. Several CFOs mentioned that improved AI tools for accounting, reporting, and compliance could allow them to handle these functions internally at a lower cost than outsourcing.

Back-Office Operations: Ripe for Disruption

Beyond fund administration, the entire back-office vendor ecosystem faces pressure:

  • Valuation consultants were cited as particularly vulnerable; many firms are already using AI-enabled valuation services like Carta with positive results.
  • Legal & Compliance services for routine work, like fund formation documents and compliance filings, are clear targets.
  • Audit and tax services are also in the crosshairs.

The Consulting Landscape

Private equity firms are assessing partnerships with various consultants, including both larger and boutique ones. The feedback has been mixed. Although these firms provide valuable expertise, there is a reluctance to pay premium fees for untested solutions.

EY got specific praise for a hands-on AI session they ran for one firm’s entire back-office team. The focus was on technology, along with teaching people to prompt effectively and identify “quick wins” achievable with off-the-shelf tools.

Talent and Organizational Structure

Here’s where it gets tricky. Everyone wants AI expertise, but no one can compete with the compensation packages tech firms and bulge brackets are offering AI talent.

Everybody agreed that instead of solely recruiting outside AI specialists, the primary goal should be to “turbocharge” and enhance the AI capabilities of existing teams.

The emerging model: leverage external expertise for discrete projects rather than building internal AI departments. Several firms have established cross-functional working groups to share learnings and evaluate tools, with representation from IT, operations, legal, compliance, and investment teams. In many other cases, it’s the CFO who leads a broader investigation into where AI can be applied most effectively and which technologies and consultants are worth considering.

The question is, how are firms upskilling existing talent at all levels to effectively leverage these tools? Will senior leadership risk falling behind if they do not build these capabilities? Are there opportunities for junior talent to advance more quickly when they master it?

The Real Objective: Scale Without Adding Headcount

Almost everyone agreed on this point: the goal isn’t huge headcount cuts. Most firms feel they already operate with lean structures, and finance departments are small to begin with (reductions often won’t move the needle anyway). The real prize is growing AUM and portfolio without proportionally growing your team.

The near-term impact will likely concentrate on junior and mid-level roles that handle repetitive analytical work, though this raises questions about developing the next generation of leadership talent if AI eliminates the “apprenticeship” phase.

AI is Here: Do You Know Where Your Data Is?

Data infrastructure was identified as the biggest constraint for many firms. Before they can fully harness the value of AI, substantial investments are needed in areas such as data cleaning, access, and standardization. The challenges they face are multifaceted and include:

  • Legacy file structures
  • Inconsistent data schemas
  • Permissioning issues
  • Cloud migration
  • System integration

While there are important data privacy concerns to address, it is also necessary to find a balance in data access. The required investment is considerable, but companies acknowledge it as essential infrastructure spending rather than optional innovation.

Looking Forward with a Measured Approach

The most exciting conversation centered on what happens 12-18 months from now, when AI can handle an entire workflow end-to-end. Not just enhancing discrete tasks but actually replacing complete processes.

The most sophisticated PE firms are taking a measured approach. The ones that seem furthest along are those:

  • Deploying enterprise tools with transparent governance
  • Creating forums for cross-functional learning
  • Focusing on “turbocharging” everyone in the firm with prompting skills and a framework for identifying practical applications
  • Avoiding expensive vertical solutions that merely wrap base models

The real progress in AI adoption stems from cultural change that empowers teams to identify and solve problems independently. Curiosity and initiative matter more than top-down mandates, making it essential to nurture a culture where your team feels empowered to find and implement solutions on their own. The strategic question is no longer whether to engage with AI, but how quickly you can get started.

The Bottom Line: AI’s Sustainable Competitive Advantage

AI adoption in private equity is neither the dramatic revolution promised by vendors nor the insurmountable risk feared by compliance teams. Instead, it’s a pragmatic, infrastructure-heavy evolution demanding cultural adaptation and patience for incremental progress.

The most competitive PE firms aren’t chasing every new tool. They’re building environments where teams are empowered to experiment and implement solutions that tackle real operational challenges.

That culture – not the technology itself – is the sustainable competitive advantage in the AI era.