AI trends in financial management

PE firms are ahead of the curve in using AI for financial operations. Almost all — 97% — of the PE financial leaders surveyed say they're using AI, compared to 76% of mid-size company CFOs.

Focused on operational efficiency, PE firms have been relatively early adopters of AI and have started to see the benefits of implementing it. The survey found that 81% of financial decision-makers at PE firms say using AI made business easier. By comparison, only 45% of CFOs at mid-size companies say the same.

While AI is a priority for both groups, more finance leaders at PE firms say they'll increase their investment in AI. This may be because PE firms are reaping several benefits. They're using AI to automate manual processes, synthesize data to help with fraud detection and assist with other financial operations. These efficiencies can reduce costs and make people more effective in their roles. In turn, the success PE firms are experiencing likely makes their financial leaders confident about AI and drives them to explore even more uses.

In mid-size companies, CFOs typically lead the way when deciding if the company will use AI. In part, as consulting firm Deloitte points out, this is likely because CFOs across all industries are under pressure to reduce costs, grow revenue and maintain regulatory compliance.¹ They're also increasingly seen as key business strategists. The growing role of the CFO makes them uniquely positioned to drive AI implementation.

The survey found that the CFO leads 87% of AI implementations for financial processes. The chief information officer (CIO) comes in a distant second, leading 41% of such efforts. A CFO who leads AI implementations typically partners with their organization's chief executive officer (CEO) or CIO.

At 76% of the mid-size firms surveyed, CFOs say they're already using AI and applying it in various ways. Over half of them report applying AI to their cash flow forecasting and financial analyses. The use does, however, vary by industry. Tech companies, for example, were the most outsized adopters of AI for cash flow forecasting at 80%. And while slightly less than half of all mid-size companies rely on AI for payment automation, 75% of healthcare companies use it for that purpose.

The variety of applications will likely increase. In customer support, AI can now analyze transcribed customer conversations to identify common complaints or questions so companies can proactively collect and address those insights.

As more industries start using both traditional AI and generative AI — which involves the tech using human prompts to synthesize new images, text and other content by drawing from vast data sets and machine-learning models — organizations are grappling with the legal and ethical implications. The survey found that legal compliance is the top concern for mid-size companies, followed closely by magnification of errors and privacy violations.

Notably, top risks vary considerably from one industry to the next. About 33% of companies in business services rank legal compliance as the most important risk, but only 5% of companies in technology, media and telecom say the same. More heavily regulated industries, such as healthcare, appear to be more attuned to potential legal risks. In healthcare, 100% of companies surveyed in the industry say they've implemented legal training.

Private equity firms are most focused on privacy violations, followed by legal compliance.

With AI developing so quickly, regulations are lagging. In-house counsel needs to be aware of gaps in regulations and laws as well as potential legal and ethical issues. A recent survey from Deloitte found that 38% of mid-cap companies don't have a board or committee with primary oversight for AI, and about half of companies don't have any employee or board education or training on AI.²

AI is transformative in helping mid-size companies reach greater operational success and efficiency. While the CFOs surveyed say they mostly use AI for cash flow forecasting and financial analysis for now, the uses will surely increase. Companies would do well to keep an eye on how trends evolve in 2024 and beyond.

Citizens worked with research firm Escalent to produce a survey that shows how financial decision-makers at mid-size companies and PE firms are thinking about AI processes and incorporating the technology in their financial operations to increase efficiency. Participants were screened for their current use of AI or their openness to using AI in the future, and those who were not using it or not interested were excluded.

• All participants worked in industries other than banking at the time of the survey.
• 127 participants were CFOs in mid-size companies with annual revenues between $50 million and $1 billion.
• 77 participants were financial leaders at PE firms with a fund size of less than $1.5 billion and were active with mid-size companies.
• Fielding was conducted with Escalent during Sept. 5-21, 2023.

During the survey, the respondents were provided with these definitions of key terms:

• Artificial intelligence: The intelligence of machines and software that can mimic human problem-solving, recognition and decision-making.
• Financial operations: All aspects of managing the finances of a business/organization, including but not limited to financial analysis, cash flow forecasting, risk management, payments, etc.
• Machine learning: A subset of AI that uses algorithmic learning to automate complex tasks such as custom recommendations, dynamic pricing, etc.
• Robotic process automation: A form of business process automation that allows a virtual bot to perform repetitive/routine tasks.