2025 AI Trends in Financial Management

How CFOs are using AI for payments and fraud detection

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Clear use cases for AI are emerging. The 2025 survey on AI in midsize U.S. companies provides new data on how company CFOs and PE leaders are using AI for payments, cash flow forecasting, and customer support, revealing their progress to date in putting these breakthrough technologies to use.

From payment automation to generative code-writing for due diligence, financial leaders are notching some “wins” on the board. Yet, enthusiasm could be waning across some users, and the onus is increasingly on CFOs alone to champion and implement AI across financial processes. Perception of legal risks has also climbed. Here’s how CFOs and PE firms deploy AI in finance functions today and what they are planning for the future.

Key insights

  • At midsize companies, the responsibility is increasingly on CFOs to champion and implement AI for financial processes. In the previous survey, tech executives played a bigger shared role.
  • Payment and fraud detection are the top use cases for AI in finance departments at midsize companies, while PE firms say they use it most for optimizations within their portfolio management.
  • More CFOs and PE firms perceive legal risks related to AI usage compared to the 2024 survey.
  • Budgets for using AI in financial processes are expected to increase.

Onus for AI in financial processes falls on CFOs

At midsize U.S. companies, CFOs are leading the way in efforts to apply AI to financial processes. While this was also true in the 2024 survey of AI trends, the new data paints an even clearer picture of CFOs as the primary driver of these efforts. Eight in 10 CFOs say they are in charge of promoting or implementing AI in their department.

In contrast, the 2024 survey suggested that there was more shared leadership across tech-oriented roles including chief technology officers (CTOs) and chief information officers (CIOs), and even from chief development officers (CDOs), who typically have responsibility for fundraising and external financial activities. The 2025 survey suggests that AI leadership is consolidating, for better or worse – and CFOs could be assuming more responsibility for strategizing and implementing AI in their departments.

  • "We are at a pivotal point in the cycle of this technology, where firms are really starting to figure how to use AI for the biggest efficiency gains and key processes in their organizations."

    Krish Swamy

    EVP Chief Data and Analytics Officer

Use cases with the biggest impact

Payment automation is ranked as the most productive use for AI in financial processes so far. 63% of CFOs say AI has made their payment automation significantly easier, a 23% increase from 2024. Fraud detection has also proven to be a valuable use case for CFOs, with nearly six in 10 saying that AI has made fraud detection significantly easier. Cash flow forecasting also remains a popular use case in finance departments.

 

  • "Payment efficiencies are incredibly valuable to midsize companies, a data point that also comes up in our annual payments surveys. Fraud detection is also a very hot topic for AI in midsize companies today."

    Bill Gold

    SVP Data and Analytics

Private equity (PE) firms that invest in midsize companies have also eagerly embraced AI for financial processes. Since PE firms are company investors rather than company operators, their use cases differ from those used by company CFOs. Portfolio monitoring, the ongoing process of tracking and managing the performance of a firm’s investments, continues to be a top use for AI, with more than half of PE firms saying the technology made it significantly easier in the past year. Many PE firms report high value in AI across a number of other processes, including exit strategies, due diligence, and investment analysis.

While adoption for AI remains high among PE firms, there was a noticeable retreat from 2024 levels. PE firms were early adopters of AI to streamline and enhance financial processes. Their waning enthusiasm could be a sign that the marginal gains of AI are diminishing with its longer use, or it could be that the reality of deploying AI is tougher than expected. It could also be driven by other causes.

Company CFOs and PE firms were both less enthusiastic about the benefits of AI for risk assessment, though many respondents submitted comments about AI’s value in error-proofing processes that are prone to human mistakes. Still, there could be some more global functionality in risk management that AI tools are not yet suited to tackle. The risks of the future are not necessarily the same as the risks of the past, which could make AI a weak practitioner since it is all trained on past data.

Use of generative AI is high, and varied

Generative AI, which can create content including text, video, pictures and music, is a narrower category of AI functionality – and it is being used by 100% of CFOs and PE respondents, according to the 2025 survey.

However, uses for generative AI differ from the broader set of AI functions. PE firms say they use generative AI most commonly for customer service, which could encompass chatbot functionalities, and for cybersecurity. CFOs at midsize companies say they are using generative AI the most for predictive analytics and cybersecurity.

  • "Generative AI will open up powerful possibilities in finance for both CFOs and private equity leaders. From predictive analytics to enhancing customer interactions, its remarkable to see this technology evolving from experimental to essential, with anticipated nearly universal adoption across midsize companies. We’re watching this innovation push boundaries, providing new ways to support decision-making, risk assessment, and customer engagement."

    Beth Johnson

    Vice Chair, Chief Experience Officer

Perception of legal risks grows

As AI has become ubiquitous in business uses, perception of the technology has evolved – not always in the most positive way. The 2025 survey revealed an increase in the perception that AI will require significant effort to identify legal and appropriate use cases, as 92% agree. Likewise, it’s more commonly agreed that AI will face significant legal barriers concerning data security, a view held by 63% of midsize company CFOs and PE firms. The 2025 survey also revealed a 10% gain in the share of respondents who think AI will make contact center jobs obsolete.

Other perceptions of AI remained more stable, including a broadly held viewpoint that AI will make it easier for stakeholders to find information, that it will become essential to business operations, and that it will generate continued cost savings.

While many are confident about AI’s value, a significant (and growing) proportion say that AI will not have a significant effect on business in the next five years, a view shared by 48% of survey respondents.

AI budgets to increase at companies and PE firms

The 2025 survey suggests a maturing understanding of an emerging technology, with more clearly defined use cases and perhaps more clearly defined expectations among financial leaders.

Among PE firms in the midsize company space, the data reflects a moderate retreat from the enthusiasm levels of 2024. Still, overall confidence in the value of AI for financial processes remains high. While spending intentions are ambitious for the five years ahead, PE firms plan to invest slightly less compared to the 2024 survey.

Midsize companies have caught up to PE firms in their confidence in the technology, and they are embracing AI investments in their budgets at a higher level in 2025 than they did in 2024. Across both groups, about seven in 10 plan to increase their current investment in AI over the next five years.

Actions to consider in 2025

  • Take these survey results to your finance teams to generate discussion about the ways that your organization could be using AI more effectively.
  • Encourage cross-functional partnership in your leadership teams to share learnings about AI implementation in different departments. Take steps to prevent AI expertise from becoming siloed.
  • Stay informed about best practices related to legal and regulatory compliance for AI. Consider forming a task force internally to monitor new developments.
  • Look at peer companies to get a sense of their AI usage in financial processes. Use that knowledge to make budget decisions for your own organization’s AI efforts.

Explanation of methodology

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.
  • 131 participants were CFOs in mid-size companies with annual revenues between $50 million and $1 billion.
  • 72 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 from August 30 – September 13, 2024.

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.
  • Generative AI: AI technology that uses human prompts to synthesize new images, text and other content by drawing from vast data sets and machine-learning models.
  • 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.

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