Xavier Fernandes, Analytics Director at Metapraxis, talks about how FP&A teams are using AI to drive changes in business performance. Xavier also mentions a couple of examples where FP&A teams were faced with ongoing disappointing business performance and what AI approach they chose.

Machine Learning provides tremendous insight regarding market trends & business drivers. These factors include market propensity, consumer demand, economic factors, weather, & transportation costs. Many companies take these variables into consideration but provide limited or time-consuming analysis.  This process limits corporate agility. 

In the video, Asif Khan, Global FP&A Lead at PayU, shares 5 steps of implementing ML for fore

Takeshi Murakami, Group Controller at Microsoft, shares an interesting case study on leveraging AI/ML in decision-making. Microsoft Finance enhanced forecast accuracy by using ML instead of the traditional bottom-up process.

FP&A teams are using AI to drive step changes in business performance, pushing their influence beyond their traditional areas of analyses.

The democratization of technologies is underway. Tools like machine learning (ML), which were confined to universities, hedge funds or investment banks just until a decade ago, are now finding their way into industry-wide applications. The finance function is set to reap the benefits of this democratization wave.