AI in Action: From Hype to Value Creation

Artificial Intelligence (AI) has long dominated conversations across the Private Equity market, but the focus is now shifting from hype to practical application. Across our conversations with Financial Sponsors, including a roundtable hosted with Baringa Partners, the emphasis is increasingly on where AI can create genuine value and how firms can apply it in a commercially meaningful way.

We also surveyed the Private Equity lower mid-market to understand where AI is currently delivering the greatest impact and what barriers remain to wider implementation. The findings reflected a market that is increasingly pragmatic. Most respondents identified operational efficiency and risk management as the areas where AI is creating the strongest value today, while relatively few linked AI directly to revenue growth or associated it with exit valuation enhancement at this stage.

That outcome was perhaps unsurprising. Across our conversations with sponsor clients, there is a clear recognition that AI’s immediate role is not necessarily to reinvent business models overnight, but to improve how businesses already operate. Much of the current impact is centred around accelerating workflows, improving consistency and helping management teams focus more time on higher value activity.

Areas such as finance operations, reporting, back-office administration and working capital forecasting are emerging as practical starting points. They offer tangible, measurable outcomes while helping build confidence for broader AI adoption.

One of the strongest themes emerging across these conversations is that AI is increasingly reshaping how work gets done, particularly across analytical and process driven environments. The roundtable conversations highlighted how many tasks that have historically underpinned professional and advisory services, from research synthesis to financial analysis and reporting, are already being automated or significantly accelerated through AI-enabled workflows.

Importantly, the debate is not simply about AI replacing people. Instead, the emphasis is on how AI changes where value sits within organisations. Businesses that have historically relied on junior heavy delivery models and time-based billing structures are likely to face increasing pressure as repeatable analytical tasks become more automated. In that environment, differentiation increasingly comes from expertise, judgement, sector knowledge and the ability to combine AI capability with commercial insight.

Another key theme was the growing importance of proprietary data. As AI tools become more widely available, competitive advantage increasingly comes from how organisations use their own data, operational knowledge and workflows to generate insight and drive better decisions. Firms that can structure and leverage proprietary datasets effectively are likely to create more defensible positions than those relying solely on generic AI tools. As a result, AI is becoming embedded into core operational processes, from diligence and forecasting through to reporting and portfolio management.

Sponsors were also realistic about the challenges involved. Our survey showed that data quality and technology issues remain the biggest barrier to adoption, followed by cyber and regulatory concerns and a lack of internal expertise. Most businesses are not struggling to access AI tools; the challenge is having the operational readiness, data foundations and clarity of use case required to deploy them effectively. Successful adoption starts with solving practical business problems rather than pursuing technology for technology’s sake.

Governance remains another critical consideration. As AI becomes more embedded into workflows and decision-making, sponsors are paying closer attention to accountability, IP ownership, cyber risk and workforce capability to ensure adoption is both effective and responsible.

Looking ahead, AI’s role within Private Equity portfolios is likely to continue expanding. While operational efficiency remains the immediate priority, many sponsors are already considering how AI can support broader commercial applications, from forecasting and pricing optimisation through to enhanced decision-making and customer insight.

The firms most likely to benefit will not necessarily be those investing most aggressively in technology, but those approaching AI with a clear commercial focus, strong operational discipline and a realistic understanding of where it can create meaningful value across the investment lifecycle. Across the lower mid-market, the conversation is becoming far less about hype and far more about disciplined, commercially focused application. That shift is already well underway.