Finance leaders are now harnessing a new type of AI to boost their return on investment. Instead of just analyzing data or generating reports, these advanced systems can act independently to handle complex tasks. This shift is changing how companies approach automation, especially in accounts payable, leading to faster processes and better results.

From Experiments to Real Results with Agentic AI

While many organizations have experimented with AI in finance, most have used it mainly for testing new capabilities. Around 61 percent of finance teams have deployed custom AI tools primarily as experiments, hoping to see if they could improve processes. However, these efforts often didn’t deliver the expected benefits, leading to frustration.

Now, there’s a push for more practical, results-driven AI. According to a report by Basware and FT Longitude, nearly half of CFOs are feeling pressure from leadership to implement AI solutions that generate measurable returns. As Jason Kurtz, CEO of Basware, explains, patience for unproven AI projects is running out. Boards and CEOs want AI that works—not just experiments that look promising but don’t produce tangible value.

Agentic AI in Accounts Payable: The Perfect Fit

One of the most promising areas for agentic AI is accounts payable. This process is well-suited because it involves structured data that can be easily managed by automation. About 72 percent of finance leaders see AP as the best starting point for deploying autonomous agents. Tasks like invoice capturing, data entry, and compliance checks are now being automated with high autonomy.

These systems are used to automate daily tasks, such as extracting invoice data and checking for duplicates or fraud. For example, some companies are deploying AI to identify and prevent overpayments or detect suspicious invoices. Success depends heavily on data quality—training these systems requires large amounts of accurate invoice data. Basware, for instance, has trained its AI on over two billion processed invoices to improve accuracy and context awareness.

Kevin Kamau, Basware’s Director of Product Management, notes that accounts payable offers the right mix of scale, control, and accountability for testing autonomous AI. Because the process is rule-based and repetitive, it allows AI systems to operate with minimal human oversight, making it an ideal proving ground for this technology.

Choosing How to Implement Agentic AI

Once organizations see the benefits, they face decisions about how to acquire these AI capabilities. Some companies develop their own systems, while others buy ready-made solutions from vendors. The term “agent” covers a wide range of tools, from simple workflow scripts to sophisticated autonomous systems that can make decisions on their own.

Deciding whether to build or buy depends on factors like data availability, budget, and specific needs. Building custom AI might offer more tailored solutions but requires significant investment and expertise. Buying off-the-shelf systems can be quicker and more cost-effective, especially if they are proven to work in similar environments.

Ultimately, the goal is to integrate agentic AI seamlessly into existing workflows. This ensures that finance teams can leverage automation not just for efficiency but also for better decision-making and faster responses. As AI continues to mature, companies that adopt these autonomous systems early will likely see significant competitive advantages in their finance operations.

Inspired by

• https://www.artificialintelligence-news.com/news/agentic-ai-drives-finance-roi-in-accounts-payable-automation/

Sources

• basware.com