FIS Research: UK Finance Leaders Back AI in Cash Management, Yet Almost a Third Cannot Measure What It Is Delivering

James Mitchell, Global Head of Office of the CFO at FIS

“Finance leaders are investing in AI with a clear sense of where it can add value; however, what we are observing is that the ability to measure that value is not keeping pace with deployment. If you cannot clearly demonstrate what value AI is delivering, it becomes very difficult to build the internal confidence needed to support a move beyond pilots and truly scale. That measurement challenge is closely linked to data quality, trust and connectivity across the enterprise. AI is only as reliable as the information it works with, and in many finance functions, that information is still being assembled manually from disconnected systems. Addressing that requires treasury and liquidity management technology that connects data across banking relationships, legal entities and financial systems. For instance, this interoperability can help reduce the manual effort involved in building a trusted cash forecast and provide AI with the reliable data foundations it needs to support measurable value.”

James Mitchell, Global Head of Office of the CFO at FIS

“Finance leaders don’t lack conviction in AI. They often lack the evidence to prove it, and you cannot safely scale what you cannot trust and measure. That measurement gap is really a data quality gap. When a cash position is assembled from disconnected banks, entities and systems, with any manual process involved, neither the finance team nor an AI model can fully utilise it until that data has been rationalised. As a result, decisions can slow down, opportunities can be missed, and confidence in AI models deployed before that work is done can erode. We expect the organisations that pull ahead to be the ones that address their data foundation and interoperability issues first. That is where FIS can help: our treasury and liquidity solutions are designed to give finance teams a consolidated, near real-time view of liquidity by connecting data across their banking relationships, legal entities and financial systems, helping to reduce manual effort, support a more trusted cash position and forecast, and provide AI with a reliable data foundation to help deliver value leaders can measure and demonstrate.”