Corporate treasuries’ AI investments
Although the ROI for finance organizations is relatively low, many have cracked the code to higher returns.
A recent survey from Bain & Company shows that less than half (48%) of senior finance executives have seen improvements in speed and cycle times since investing in artificial intelligence (AI) within their treasury organizations, and nearly a third (34%) have seen headcount efficiencies and cost reductions.
Over the past 12 months, most enterprises have discussed AI use cases for accounts receivable, treasury, and accounts payable in corporate treasuries, and have experimented with AI extensively. “They’ve approached it more of a ‘Here’s an intelligence, let’s see how we can incorporate it into our business’ concept,” said Rami Chahine, chief product and technology officer at treasury-automation vendor Serrala.
According to the Bain study authors, this is a common situation within finance departments. Of the survey respondents, approximately 12% of finance organizations have deployed machine learning in financial planning and analysis (FP&A) forecasting in production.
“Yet in many cases, the underlying process has not changed,” the authors wrote. “Finance teams run AI-generated forecasts alongside existing bottom-up planning cycles: two processes running in parallel, neither completely reliable.”
As a result, these finance organizations do not realize the expected benefits of faster cycle times, fewer people-hours, or greater accuracy.
AI can’t fix GIGO
According to the authors, this is not a technical problem. “This happens when AI is layered over existing ways of working rather than providing incentives to change them. If this workflow debt is not addressed, AI and automation could increase complexity rather than productivity,” he wrote.
Other issues that act as barriers to AI investment include concerns about trust, data sovereignty, and the ability of companies to audit AI’s data use.
AI is built to learn, but CFOs are concerned that only their instance of AI is using their proprietary data only to answer their questions, rather than teaching other AI instances to answer someone else’s questions, Chahine said.
“Everyone understands the power of agent AI and its ability to take over some of these manual tasks in the financial automation and treasury process. But the biggest concern that will truly impact adoption is whether we can trust it.”
Despite these issues, CFOs are enthusiastic about AI investments in their organizations.
More than half (56%) of CFOs surveyed are increasing AI investments by more than 15% this year. When the window is extended to two years this figure increases to 83%, with 42% of respondents expecting AI spending to increase above 30% over the same period.
