A pragmatic approach to digital transformation

Investors increasingly expect finance functions to deliver faster, sharper insights that support commercial agility, integration, and exit readiness. Yet, as portfolio companies seek to modernise their finance operations, many are tempted by the promise of artificial intelligence (AI) without first addressing the more foundational challenges like disparate systems and manual processes. Rather than chasing the most advanced tools, finance leaders should focus on solutions that are fit-for-purpose, whether that’s automation, machine learning, analytics as opposed to general catch all term of “AI”, to build resilient functions that scale with business growth.

Many of our clients are under pressure from Directors and management to implement AI into their businesses processes. While some have successfully implemented small scale projects in tightly-controlled data environments, others have recognised that they have a low-digital maturity and require significant investments in data governance and security.  We’ve been working with these clients to implement low-risk solutions across their financial function to strengthen controls, improve reporting speed, and free up capacity for value-add activities and more advanced technologies.

Reducing inefficiencies and unlocking significant gains

The transformation journey for finance teams doesn’t need to be disruptive or expensive. Many finance teams can unlock significant gains using tools that don’t require deep AI capabilities or major system upgrades. As an example, we recently supported a global professional services firm that was struggling to manage multiple finance systems and manual workflows that had delayed billing, collections, and cash forecasting. These inefficiencies were creating real cash flow constraints and increasing error risk. By enhancing the existing finance system’s capabilities and automating key working capital processes, we helped this client accelerate their cash conversion cycles, improve data accuracy, and unlock over $25 million in working capital. We also helped to establish a scalable foundation for future digital tools .

Another $600 million turnover client operating across 200 sites, implemented a machine learning–based decision tree to optimise workforce rostering. Previously, each site manager prepared rosters independently, leading to inconsistent quality and inefficiencies. By applying machine learning, the client automated roster preparation to replicate the best site manager’s approach across all locations. This innovation not only improved scheduling accuracy and resource utilisation but also freed managers to focus on higher-value activities, demonstrating how targeted technology solutions can deliver tangible benefits without requiring wholesale system overhauls.

AI is not a silver bullet

AI is not a universal, one-size-fits-all solution. Introduced too early, it risks adding complexity and noise but when layered onto strong processes and clean data, AI and the associated technology solutions can elevate finance processes from efficient to truly strategic. The real value of machine learning lies in how it enables people to deliver better decisions, faster.

We recently supported a large services client in developing an AI-driven fraud detection capability that replaced traditional red flag reviews with a more sophisticated, risk-weighted approach. Faced with large, fragmented datasets across multiple platforms, the client struggled to detect emerging fraud risks in a timely way. Our team designed and implemented a layered solution to synthesise data, identify anomalous behaviours, and assign dynamic fraud risk scores. A live dashboard visualised these outputs, allowing the finance team to triage investigations efficiently and reduce false positives. This tool not only improved fraud detection accuracy but also built internal confidence in the responsible use of AI. The system is now iterating to keep pace with emerging fraud patterns.

For private equity investors, the most sustainable value creation often starts with right-sizing the solution to the complexity of the problem. The future of finance isn’t about chasing the next big technology trend. It’s about building a function that is decision-ready, scalable, and resilient to support commercial agility and exit readiness. When technology is fit-for-purpose, it can deliver results faster and with lower risk. Because in the end, the real value lies not in the sophistication of the tool, but in its ability to deliver measurable impact.