BOTTOM LINE UPFRONT
The finance function continues to expand in scope and importance. At LevelOP in Europe, leaders emphasised the need to pair strong finance fundamentals with high-quality data, disciplined execution, and targeted AI adoption. Together, these capabilities are helping firms build more scalable finance organisations, support value creation, and maintain readiness for whatever comes next.
The private equity finance function is under more pressure than it has been in years. Sponsors want faster insights, cleaner data, and AI adoption that shows up in results. CFOs are being asked to do more, know more, and move faster, all while keeping the foundational work running at the same standard it always has.
Amidst pristine Surrey Hills, LevelOP put all of it on the table. Here’s what came out of the room:
1. Finance fundamentals are still the price of admission
The AI conversation is loud. But conversation kept returning to the basics: forecasting quality, reporting reliability, data integrity, cash visibility. At this point, these are table stakes.
The pattern most cited: strong trading masks weak finance foundations. Those gaps surface during diligence, refinancing, or exit, and by then remediation is expensive and often too late.
2. The CFO mandate keeps expanding without shedding its existing weight
CFOs are still accountable for everything they were five years ago. They’re also now expected to be strategic advisors, data stewards, technology champions, and exit architects. All at the same time.
And the hiring bar is shifting too: sector experience and technical capability still matter, but firms are increasingly screening for intellectual curiosity and learning agility alongside them.
3. AI is moving from experimentation to execution
No one’s asking whether to use AI (they know the answer is yes). They’re asking where it can be used safely and effectively. FP&A, board pack preparation, financial analysis, workflow automation: use cases are multiplying. The job is identifying opportunities, managing risk, and ensuring technology delivers measurable business value.
One nuance worth holding: AI can surface analysis and recommendations, but accountability for what gets trusted and acted on stays with the CFO. The tools are moving fast, but the accountability is not.
4. Data is the foundation, and most organisations aren’t ready
AI can accelerate analysis and automate workflows. It can’t fix bad data. The limiting factor in most organisations isn’t the technology itself, but what’s underneath it. Many firms are focused on AI tools while the more advanced ones are working on source systems, data architecture, process maturity, and governance. The practical implication raised repeatedly: most organisations think they have an AI problem when they actually have a data and ownership problem.
5. Finance Operating Partners are becoming more embedded and more scalable
The role continues to mature. Involvement used to mean crisis support or periodic reviews. Increasingly, firms are adopting structured engagement from Day 1, spanning executive onboarding, continuous portfolio engagement, and capability building. CFO forums, peer networks, and portfolio-wide communities are becoming deliberate tools for accelerating development – because CFOs learn most effectively from peers who’ve faced the same problems.
6. Exit readiness is an outcome, not a project
Exit readiness is a controversial term. It can be framed as a critical workstream; or it can be argued the term is overused and that exit readiness is just the by-product of running a strong finance function throughout the hold period.
Either way: clear value drivers, robust reporting, forecasting discipline, high-quality data, effective governance, and a compelling equity story shouldn’t wait until the final stretch. Build them now; the firms treating exit readiness as a project are already behind the ones treating it as a standard.