Staying in tune with consumer demands can be challenging, especially when these demands change almost daily. Tracking consumption patterns to predict demand is a monumental task. Previously, solving this problem involved spreadsheets or legacy statistical methods. But with automation and machine learning, artificial intelligence can help organizations slice through mounds of data to get more accurate and timely insights on consumer demand . Machine learning can build forecasts for hundreds of thousands of items and consider all of the minute details for each one of them, from seasonality to sales history. For example, automated machine learning can easily create separate models on clusters of products, using unsupervised ML techniques, to make predictions even more granular such as by store, week, and SKU.