The finance function is undergoing a fundamental transformation, and it's happening from within ERP itself. Modern cloud-based financial management systems like Sage Intacct, the leading ERP platform designed specifically for finance teams, are now embedding artificial intelligence directly into core accounting workflows.
Features already in production include anomaly detection in the general ledger, OCR invoice capture in accounts payable, intelligent cash applications in accounts receivable, natural language queries for financial data, and more. Sage plans to roll out even more ambitious features by 2026. Autonomous workflow orchestration that can draft journal entries for review and what Brenda Kahier of financial technology consultancy Armanino calls “fully autonomous close and finance operations.”
But here's the challenge. The technology is ready, but most organizations are not. At the recent CFO Leadership Financial Accounting and Technology Expo in New York, Kaia and colleague Carmel Wynkoop explained to finance leaders the practical realities of implementing AI-driven ERP. Citing their sobering statistic from a recent MIT study, Wynkoop says, “95% of organizations fail proof of concept with AI.” reason? “They failed because they couldn't identify the right use case.”
For CFOs navigating this transition, success will depend less on the technology itself and more on how they approach implementation. Here's what they say actually works:
Please fix it before automating the process. The biggest risk when implementing AI-driven ERP is not the technology, but automating dysfunction. “Don't speed up a bad process,” Wynkoop warned. “Make sure your processes are strong and reliable.” AI amplifies whatever you input, whether it's an efficient or chaotic workflow. Before enabling AI capabilities in ERP, CFOs must ensure that the underlying processes are healthy.
Make sure humans always have the latest information. One of the most dangerous assumptions CFOs make is that the increasing sophistication of AI will allow them to operate without supervision. “You want to be Iron Man, not Hulk,” Kaier said. In the Iron Man model, humans continue to engage, communicate, and collaborate with AI. Hulk model? “He has no memory of what happened, it just happened, and neither he nor the humans know how it happened.”
The risks are not limited to immediate errors. Over time, Kahier warned, “if you get to the logical endpoint, at some point no one will understand how that bot works because they never did the work, they never built it.” For CFOs, this means building validation protocols today to maintain organizational knowledge and accountability, even when AI provides the right answer.
Start small and continually measure. CFOs must resist the temptation to tackle the biggest problems first. “You need something that you can quickly assess the value of, so make small incremental changes at first, but the ROI will pay off,” advises Wynkoop.
Identify use cases that generate rapid success and enthusiasm within your team. Document time savings, error reduction, and increased productivity. Then use those metrics to build a business case for broader adoption. Without measurement, you can't demonstrate success. And without proven success, we won't be able to secure resources for the next phase.
Recognize that data quality is the foundation. “You can't go from scratch to AI,” Kaia says. “If your data isn't in good shape, if you don't have alignment across your organization on what success looks like…that's a big problem.”
Before implementing AI-driven ERP capabilities, CFOs need to audit data quality. Is historical information accurate and consistent? Are naming conventions standardized? Do different departments define key metrics in the same way? The quality of your AI is determined by the data you use to train it. Degradation of data quality becomes apparent quickly.
Integrating AI into ERP like Sage Intacct provides transformative capabilities for finance functions, from continuous close processes to real-time predictive analytics. But technology is only half the equation. Success requires discipline: clean data, healthy processes, human oversight, and careful implementation. For CFOs who do this foundational work, the rewards are significant, including faster closings, improved forecasting, and the ability for finance teams to focus on strategy rather than deal processing.
