Since the world has come to know the fact that there can be a time when we all may have to be stuck at home, there is no denying that every industry has undergone tremendous alterations and modifications. The world of fashion is no exception, and it has also changed drastically since the outbreak. As a result, all the non-essential businesses were forced to shut down to restrict the spread of the pandemic. With all the shopping malls, streets, and retail stores closed worldwide; the situation led to the dissertation of the fashion retailers out of regular business for months. This further led to a tremendous surge in online sales as more and more people started resorting to eCommerce during the quarantine.

AI has a variety of potential applications in the supply chain. Purchase requests might be handled by chatbots, inventory could be managed by intelligent warehouses, and shipping could be assisted by autonomous cars. According to a McKinsey survey conducted in 2019, most businesses using AI saw a rise in sales: Respondents frequently mention expenditure analytics and sales and demand forecasts as supply-chain management use cases that result in revenue.

Smart analytics solutions can offer valuable insights from the data collected historically, such as browsing data, earlier purchases, and wish list items. This further allows retailers to offer their customers personalized product options, discount offers, and seasonal details to enhance their overall experience. How businesses can leverage the massive amounts of data created in their supply chain networks is today's problem. A typical supply chain accessed 70 times more data in 2022 than it did only five years prior. But just around 25% of this data was being examined. Additionally, whereas 20% of all supply chain data is structured and easily analyzable, the remaining 80% is unstructured or dark data. Organizations today are looking for the best methods for analyzing these dark data.

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