The race to bring artificial intelligence into nearly every aspect of business continues, and no department is looking for more talent than finance. Centuries of manual and semi-manual human effort in the finance sector has been hit hard by years of labor shortages that show no signs of slowing down.
That promise gave the floor of the Jacob Javits Convention Center on Manhattan's West Side a giddy gold rush atmosphere this week. About 2,000 attendees filled two football field-sized pavilions packed with vendors for CFO Leadership's 2nd Annual Financial Accounting Technology Expo.
The fact that FATE has more than doubled in size in just one year and is on track to double again by 2026 tells you everything you need to know about the demand for determining which technology vendor is best suited for financial shops and their challenges. As any CFO who has replaced an ERP will tell you, software commitments in finance are like getting married in states with 18th century divorce laws. Software replacement is not for the faint of heart.
Here are some takeaways from this week's FATE floor and AI for Finance workshop.
AI matures. The great agent future promised to all of us is still more of a work in progress than many vendors would like to admit, but it will likely arrive in 2026. I spoke with several CFOs at midsize companies who have implemented AI-powered workflows in 2025. They could also be a generative AI version of a robotic process automation type of project that helps with closing and coordination, but with more flexibility and adaptability.
Trust is fostered. The adaptation of this kind of innovation absolutely speaks to a much larger and more important trend on display at FATE. This is a general shift in tone around the fundamental question of whether AI is, or will ever be, predictive enough to be used in financial data.
This week's cliché. If 6-7 is being repeated endlessly among middle schoolers, it's the recent MIT study that found that 95 percent of all AI pilot projects ever had no measurable impact on the bottom line, and the fact that “AI will only get better from here” won out over “most often said” at FATE, which speaks to both the early days and optimism of AI's early stages.
New entrants versus established giants. As new AI-native ERPs like Campfire threaten to disrupt the foundation of all business software with the promise of smarter, more streamlined out-of-the-box experiences, the biggest question at FATE was whether established giants would quickly pivot to roll out new features and maintain their massive installed user bases. The jury is still out, but given the costs and challenges of such a switch, it will be up to major companies to prove whether they will become the Netflix or Blockbuster Video of financial technology.
Actual agent. As anyone reading this knows, unlike traditional software such as Excel, generative AI is fundamentally probabilistic rather than deterministic. This means that people who need $1,000 in paid income will only get $1,000 no matter where they go in the record-keeping and analysis process, and they'll struggle with strange changes and unauditable results. This landscape is rapidly changing, with many vendors mixing deterministic workflows with generative and/or agent “layers” to play to their strengths and crack the code.
It's happening. For example, at AWS, Lindsay Drake, CFO/VP of Finance at AWS Applied AI Solutions, created a number of in-house finance agents. This includes an agent called Neo that reduced the 15-minute adjustment time for approximately 35,000 instances to one minute, and reduced the typical four-plus hour time it takes to identify anomalies to 15 minutes. They are planning even more ambitious projects, she told participants at the AI in Finance forum. They pull all the numbers into a database in a more traditional way, allowing generative AI to pull the data and analyze it. period. “They're not allowed to do math. They're not good at math,” she says. “We don’t want LLMs to be creative.”
Data remains the core. Of course, without clean data this is not possible. This remains the alpha and omega for potential technology advancements in the financial industry. For large companies and ambitious mid-sized companies, that means hiring data engineers to bring order. For small businesses, that likely means companies like Preql, a startup that helps you make sense of disparate feeds, so revenue is still revenue, as CEO and co-founder Gabi Steele said at the AI in Finance Forum. “The single source of truth issue remains unresolved, but I believe it will be resolved,” she said. “And you can be that leader, too.”
CFO leadership can help.Despite all these great technological advancements, financial technology remains a major challenge. To support this, the CFO Leadership Council and Duke Executive Education, a division within Duke University's Fuqua School of Business, announced a strategic partnership at the event and launched a new Financial Accounting Technology certification.
The certificate program consists of 10 virtual modules,It includes deep dives taught by Duke University's expert faculty, providing an academically rigorous and hands-on learning experience. Other modules leverage peer-led insights and industry-relevant content from the CFO Leadership Council. Learn more about the program >
