AI-Enabled Rolling Forecasting Enables Intelligent xP&A

Despite the rapid pace of adoption, many Finance leaders believe that FP&A teams must learn AI and machine learning (ML) modeling techniques when attempting to deploy AI-enabled rolling forecasts across the enterprise.  Further, for organizations with existing AI investments, FP&A teams generally lack the dedicated business analysts and data science engineers required to build ML models.  And as the adoption of AI and ML for rolling forecasts moves from fiction to fact, many FP&A teams are asking the same basic question: Where to begin?

To start, don’t let AI market noise derail the evaluation process.

Here are 3 steps to consider in the process:

• Start with a clear understanding of “what” business outcomes your FP&A team is trying to achieve with AI and ML.
• Identify “who” is using the solution.
• Consider “how” the solution is unified into existing planning processes.

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