AI in SAP S/4HANA Finance: 3 Practical Use Cases for Measurable Business Value

Artificial intelligence has become one of the most frequently discussed topics in enterprise finance. The conversation usually begins with automation, productivity, and the possibility of generating faster insights. However, in the finance transformation projects I have worked on, the more important question has always been much more practical. Finance organizations rarely suffer from a shortage of AI ideas. What they often lack is clarity on where AI can deliver measurable business value. The more difficult challenge is selecting the right use case, establishing a defensible baseline, preparing the data, integrating the technology into existing controls, and persuading users to trust the resulting recommendations. Through my work on SAP finance transformation, reporting, analytics, process standardization, and data governance initiatives, I have learned that the most successful AI implementations are not necessarily the most ambitious. They focus on a clearly defined business problem and a well-understood transaction population. They also establish measurable outcomes before implementation begins. This article examines three areas in which I have seen AI and intelligent automation...