Gavin Hinks
CFOs have been urged to take care with how they attempt to apply artificial intelligence (AI) in their finance operations as research reveals that most of last year’s projects to introduce the technology did not make it over the line.
According to market intelligence firm IDC, while CFOs believe that AI can address key concerns such as the speed of decision-making, managing compliance and risk, and coping with meetings overload, only 13 per cent of implementation projects were successful in 2024.
Experts point out that identifying the specific situations where AI could be deployed, known as "use cases," requires finesse.
Michael Lengenfelder, global solutions architect at Unit4, a software company that sponsored IDC’s research, says that there is a "real danger" that many applications of AI are aimed at accelerating workflows already well managed by other technologies, such as using the technology for forecasting on factors that undergo minimal fluctuation.
"Identifying use cases is not straightforward," he says. "We always advocate a pragmatic approach starting with understanding the problem you want to solve, but at its heart this is a calculation around balancing the expected benefits against the costs of implementing AI to understand what the most cost-effective use case will be."
AI’s limitations
CFOs also need to be aware of tasks not suited to AI, such as analysing information that requires the kind of knowledge and experience held by different teams. "Could an AI tool realistically dig into multiple layers of data to uncover this information as quickly as an experienced finance professional?" Lengenfelder asks.
Lengenfelder singles out financial planning and analysis as a specialism not suited to GenAI as the technology relies on the use of large language models (LLMs), which looks for patterns but struggles to accommodate random events. "It is difficult for AI tools to take account of unexpected events such as extreme weather or seasonal fluctuations," he says. "As a result, there is a danger that such an AI tool might forecast resources being allocated to projects consistently without reflecting the realities of external factors affecting a business."
DeepSeek impact
Discussion of AI has come to dominate the business landscape as corporate leaders investigate whether it will either disrupt industries or provide efficiencies that will allow companies to get ahead of competitors. Governments plan to invest heavily in AI, too.
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However, the AI world was also upended in January by the release of Chinese AI DeepSeek, using lower grade chips and said to have cost a fraction of the investment pumped into pioneers like OpenAI’s ChatGPT. DeepSeek’s release saw millions wiped from tech stocks around the world as investors struggled to clarify its implications for the industry.
Companies remain in learning mode, too, about the most effective ways to use AI, and that means placing possible use cases und
