2026 AI Trends in Financial Management

AI Adoption and Investment Momentum Grows

The proportion of midsize companies (defined as organizations with annual revenues between $50 million and $1 billion) that plan to increase their AI investments over the next five years has increased over the past three surveys, from 58% in 2023 to 82% in 2025.

Just as importantly, midsize companies are seeing their realized ROI begin to match their lofty expectations. In 2025, respondents reported an average 35% ROI, a figure approaching the 41% they state would be needed to consider their AI investments a success. Furthermore, 61% of midsize company CFOs agree that AI has made financial processes easier, a significant uptick from prior years (just 38% in 2024).

Firms replace outsourcing with internal development and usage

This growing enthusiasm around deploying AI is driving more companies to bring their development in-house, a trend most notable among PE firms. The percentage of midsize company CFOs that have partnerships with external firms that utilize AI declined from 64% in 2024 to 58% in 2025, while for PE firms, the figure has fallen from roughly three-quarters (76%) to slightly over half (52%).

Concurrent with this trend is a growing acceptance of AI usage among employees, as fewer than a quarter of staff at both midsize companies and PE firms now oppose using AI in the workplace.

The Rise of Agentic AI

An unknown in prior surveys, agentic AI appears ready for its closeup in 2025. This year, 82% of midsize companies and 95% of PE firms have either begun or plan to implement agentic AI in their operations in 2026. This emerging technology has proven adept for a variety of financial use cases. Both midsize companies and PE firms are leveraging this technology for cybersecurity, fraud detection, and financial planning and analysis. Mid-market companies are also deploying agentic AI for marketing support services, while PE firms are seeing success in portfolio management, regulatory compliance monitoring, and collections outreach.

Of those organizations that have already adopted agentic AI, nearly all (99%) agree it has improved their operational efficiency and workforce productivity.

How Companies Are Using AI for Fraud Prevention

Consistent with prior surveys, fraud prevention continues to be a major AI use case for both midsize companies and PE firms.

Midsize companies deploy AI to fight fraud in multiple ways

Among midsize companies, 45% are currently using AI for fraud detection, a slight decrease from 2024 (48%), but higher than the 35% reported in 2023. These organizations use AI in a variety of fraud-fighting scenarios, including cybersecurity, customer identification, real time transaction monitoring, and phishing or other impersonation scam detection.

PE firms partner with external firms that utilize AI for fraud prevention

A higher percentage of PE firms identified fraud detection as a short-term benefit of AI in 2025 (62%) as compared with 2024 (49%). Furthermore, fraud monitoring and detection is the primary way PE firms are partnering with external firms that utilize AI (71% in 2025, versus 58% in 2024), bucking the overall trend of bringing more AI use cases in-house.

For Private Equity, AI is a Plus

With encouragement from the C-suite, board, and investors, PE firms are demonstrating a growing interest in adding AI-enabled companies to their investment portfolios.

In 2025, 23% of PE firms say that at least three-quarters of the companies in their portfolio utilize AI, up from 8% in 2024. Additionally, 97% say that it is somewhat/extremely attractive if a company they are looking to add already has a successful AI strategy.

This interest makes strategic sense, as research from McKinsey shows that 39% of organizations report a positive earnings impact from deploying AI at the enterprise level.

Prioritizing Customer Outcomes in AI Implementation

Both midsize companies and PE firms cite increasing customer satisfaction as a critical measure of success for the implementation of AI within their business.

Midsize companies and PE firms agree that increasing customer satisfaction is a more important hallmark of successful AI implementation than gaining an advantage over their competitors. Additionally, customer service is the primary way midsize companies are leveraging external firms that utilize AI.

Notably, although the percentage of respondents citing "enhancing customer service" as the top motivating factor for implementing AI remained essentially flat (from 14% in 2024 to 13% in 2025), the percentage that cited it as a top three motivating factor actually increased year over year (from 37% in 2024 to 40% in 2025). This places "enhancing customer service" as the factor with the highest proportion ranked in the top three, ahead of "increasing employee availability" and "reducing risk of human error in financial analysis."

Actions To Consider In 2026

• Explore using agentic AI in your financial processes to improve operational efficiency and workforce productivity.
• Use these survey findings as a launchpad for robust discussions with your broader finance teams around integrating AI more deeply into your financial processes and daily operations.
• For PE firms, add "AI maturity" to your portfolio firm vetting criteria.
• Ensure that your external fraud monitoring partners are employing the latest AI-enabled technology to stay a step ahead of the cybercriminals.

Explanation Of Methodology

For the third consecutive year, Citizens worked with research firm Escalent to survey how financial decision-makers at midsize companies and PE firms are thinking about AI processes and incorporating the technology to enhance efficiency in their financial operations. 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.
• 152 participants were CFOs in mid-size companies with annual revenues between $5 million and $1 billion. However, only data from the 134 companies with annual revenues between $50 million and $1 billion are displayed in this report for trending purposes.
• 153 participants were financial leaders at PE firms with a fund size of less than $1.5 billion, and active with the acquisition and sale of U.S.-based companies with annual revenues between $50 million and $1 billion.
• Internet-based surveys were conducted with Escalent between October 13 and October 23, 2025.

All survey 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.
• Agentic AI: Intelligent systems capable of making complex decisions independently and automating dynamic, multistep processes.