The Business of Fashion
Agenda-setting intelligence, analysis and advice for the global fashion community.
FRANKFURT, Germany — The artificial intelligence revolution has arrived and it should not worry anyone. AI is changing jobs (not replacing them) and augmenting human tasks in consumer goods, manufacturing, customer service and many more verticals. In retail and fashion, the biggest opportunities are in trend forecasting and better supply chain management.
It’s true that IT and customer service have been the first areas to see real change from the application of artificial intelligence to trim costs and increase efficiency. Last year, however, a number of brands, including the direct-to-consumer label Everlane, backed off after adopting AI-powered chatbots, because customers found them frustrating to use.
AI offers tremendous possibilities to better serve customers and drive profits for fashion, but it’s important not to jump in too early in an area like customer service, which could very well be the thing that saves fashion brands and retailers from the onslaught of Amazon and Baidu.
But success for brick-and-mortar stores now depends on how sales events are orchestrated and managed — and that means accurately predicting discounts to drive in-store shoppers. This is just one area where AI can shine: not only optimising markdowns, but also determining the geographic allocation of stock, taking into account distribution and the supply chain.
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Behind many fashion brands is a highly complex supply chain. The infamously fast-to-fabricate H&M hit a drop in sales last quarter, and told shareholders that it was sitting on $4.3 billion in unsold merchandise. This is a problem that AI can solve.
With AI-empowered decision making, large amounts of surplus product need not happen again.
You see, in supply chain management, the brands learn by doing and processes improve over time. The thing you don’t want is to lose retained knowledge within the organisation and have to build again from the ground up. Fashion planners calculate steps and procurement follows cycles from past experience. This is also true for the people who have designed the supply chain.
By adding AI, a brand can retain knowledge of sales trends (assuming software already tracks which products sell, which don’t, and how they’re priced) to more effectively automate forecasting. Fashion is a dynamic and competitive environment, but with AI-empowered decision making, large amounts of surplus product need not happen again.
London-based EDITED is a retail technology company that helps the world’s leading brands have the right product at the right price, at the right time. At Fashion Week, they turned their AI to trends on the runway and found references through composite imagery tracking colour, texture, print or form.
While their machine learning proved that a brand’s identity can be accurately assessed in this instance, imagine how larger brands are turning the same capabilities to the web’s repository of broad consumer images posted via social media. Millennials in particular gravitate to the image for expression first, and often in place of text. And smart devices like the Amazon Look will feed data.
AI-enabled companies are currently working across shopping apps, AR and computer vision-driven image recognition, predictive inventory and more. Today’s targeting mechanisms will work even better with these visionary technologies in the future as more data becomes available to providers. The next decade, I’m excited to say, will be defined by a return to the old values of excellent customer relationships and with the added win of more effective supply chain management.
Chris Boos, lead researcher and chief executive of Arago, a German artificial intelligence leader.
The views expressed in Op-Ed pieces are those of the author and do not necessarily reflect the views of The Business of Fashion.
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