Where CFOs are seeing the first returns on AI

AT A GLANCE

• 64% of middle-market companies now have a dedicated AI budget line
• The top AI investments are accounts payable automation, cash forecasting, and fraud screening
• Median payback expectations are less than 12 months
• Approximately 70% of companies are redeploying finance talent to higher-value analysis rather than reducing headcount

Artificial intelligence continues to dominate boardroom conversations. According to a recent CFO survey of treasury and cash management, 64% of middle-market companies now have a dedicated AI budget line.

But most middle-market companies are taking a far more practical approach to this technology than the headlines suggest. They aren’t directing their first AI investments toward experimental use cases or large-scale transformation initiatives. Instead, they're focusing on areas where results can be measured, performance can be monitored, and returns can be demonstrated quickly.

For many organizations, that means starting in the back office – specifically, finance operations.

As executives evaluate AI opportunities across the business, finance operations come with a unique advantage: success is measurable. In fact, the median payback expectation on these deployments is under 12 months.

Processes such as accounts payable, cash forecasting, and fraud monitoring generate structured data, established performance metrics, and clearly defined workflows. That makes it easier to evaluate the impact of technology investments and determine whether they're delivering value. And for finance leaders, that’s what makes the investments possible in the first place.

Rather than investing in solutions with uncertain outcomes, many organizations are prioritizing use cases where improvements can be tracked through operational metrics, time savings, forecasting accuracy, and risk reduction. The result is a more disciplined approach to AI adoption – one focused on business outcomes rather than technology alone.

The research revealed three finance-related applications as the most common destinations for AI spending:

Accounts payable automation
AI is helping finance teams automate invoice capture, matching, routing, and exception management, allowing employees to focus on exceptions that require judgment rather than routine transactions.

But invoices processed per employee isn’t the only number AI is helping to improve. It’s also resulting in fewer exceptions and stronger vendor relationships by ensuring accurate invoices are paid on time.

Cash forecasting
Cash forecasting remains one of the most important responsibilities for finance leaders (and one of the most time-consuming).

AI-enabled forecasting tools can continuously incorporate actual payment and receivable activity, helping organizations improve forecast accuracy while reducing the manual effort required to update projections. That means finance teams can spend less time assembling forecasts and more time acting on the insights those forecasts provide.

Fraud screening
As payment fraud continues to become more sophisticated, finance leaders are looking for additional ways to identify suspicious activity before funds leave the organization. AI can help detect payment anomalies, unusual transaction behavior, changes to vendor instructions, and other potential warning signs that may warrant further review.

For many organizations, strengthening payment controls and reducing fraud exposure represents one of the most compelling AI use cases available today – and it often pays for itself the first time it holds a payment that a busy human would’ve released.

One of the most interesting findings from the research is what companies are doing after creating AI efficiencies.

Rather than reducing headcount, approximately 70% of organizations reported redeploying their finance resources. Hours previously spent processing invoices, updating spreadsheets, and assembling reports are being redirected toward higher-value activities such as profitability analysis, working capital management, scenario planning, and strategic decision support.

This may be where the long-term value of AI becomes most visible.

While efficiency gains are important, they’re limited. Many finance leaders are discovering that the greater benefit comes from giving their teams more time to focus on planning, forecasting, and helping leadership make informed decisions.

The companies seeing the greatest success with AI tend to share several common characteristics:

• They start with processes that already have measurable performance indicators
• They focus on solving specific business challenges rather than implementing technology for its own sake
• They establish clear expectations for return on investment
• They identify ownership and accountability before launching new initiatives
• They have a plan for how newly created capacity will be used once efficiencies are realized

In other words, they approach AI like any other business investment: with defined objectives, measurable outcomes, and a clear understanding of how success will be evaluated.

As AI adoption continues to expand across the middle market, leadership teams should consider several important questions:

• Which finance processes consume the greatest amount of manual effort today?
• How much time does your team spend gathering information versus analyzing it?
• Could cash forecasting be improved with more timely visibility into payment activity?
• Are existing fraud controls sufficient for today's risk environment?
• If efficiencies were created tomorrow, how would your organization put that new capacity to work?

Your answers can help identify where AI may deliver the greatest value for your business.

Modern finance operations rely on more than technology alone. They depend on how payments are managed, how cash is monitored, how risk is controlled, and how information flows throughout the organization. That's why the companies adopting these AI solutions often look beyond individual tools and evaluate the broader financial infrastructure supporting their business.

At M&T Bank, we help clients see that view. By bringing together expertise across treasury management, payments, fraud prevention, and working capital management, businesses can identify opportunities to improve efficiency, strengthen controls, and support better financial decision-making. Instead of simply deploying new technology, they’re using it to build stronger, more informed finance operations.

Contact your relationship manager to learn more or set up a discussion.

Source: Sawbux 2026 CFO Survey of Treasury and Cash Management