Which areas can AI be used practically, in the Fashion Industry?

Written by Maavrus

October 17, 2022

Fashion Industry

Video Transcript

Hi. Good morning. McKinsey estimates that the global fashion industry revenues this year is likely to be around $2 trillion. And it is also estimated that the investment of the fashion industry in AI and related technology is likely to be around $7 billion this year, which is 2022, which essentially means that around zero three to 00:35 percent of the fashion industry revenues is getting invested in AI, which is huge.

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Which areas can AI be used practically, in the Fashion Industry?

And AI is finding usage across the buy, move and sell functions of the fashion industry. On the buy side of it, fashion designers are leveraging AI to generate novel fashion designs through Gans, which is a generative adversarial network, which enables them to build further on that and increase their heat rates of success rates. It is used by buyers to understand and forecast trends, create the right range and take decisions related to the order quantity and the price range in which they need to operate for their target consumer segment, which essentially enables them to improve their overall GMROI for the categories that they lead. From a move perspective, AI is being used for production planning, scheduling, and dispatch scheduling. It is used for the design of ratio packs, which can be customized for the various geographies in which the fashion company operates. It is used in replenishment logic to reduce the stock imbalance in stores so that one can maximize availability while minimizing for stockholders. And from a metric perspective, it means that one is trying to reduce the distance traveled per unit of product that is sold. From a sales perspective, companies are using it to increase their marketing ROI by leveraging personalized recommendation engines. Companies are engaging with customers with the relevant product recommendation, and the relevant content, ensuring that whatever they recommend is very contextual in nature. And it uses the type of mediums and channels where it is likely to see the maximum connection with the customer. From a metric perspective, it means that by using AI in customer engagement, one can look to increase the conversion in stores and increase the website-to-order conversion on eCommerce sites and applications. In the forthcoming video series, I will talk about each of these particular functions and the AI use cases in greater detail, giving some examples of industry-leading efforts in these areas. I hope you find it useful. Thank you.

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