“AI and Retail” was the topic of this AI Monday.
And since the German government wants us to shop like frenzy, by reducing the VAT until the end of the year, we thought to focus on the Retail industry fits actually pretty well.
Despite this, the retail industry is actually one of the earliest industries understanding the value of AI.
As many stores see declining revenues or even close, surviving retailers are recognizing the need to invest in tech that promises to improve productivity and profitability. Autonomous & unmanned checkout was a notable trend in the past. Now it is computer vision and AI: better shopper and inventory tracking, enabling new customer-friendly, often cashier-less checkouts.
But also, to process consumer insights will be crucial, and boosting supply chain speed will become a priority. AI-driven demand management can also not just improve laser-sharp margins, but also tackle the increasing customer demand in a more sustainable – more circular, less waste prone society.
AI will enable a more personalized product recommendation even the whole online buying experience. Some brands like Adidas have already developed on-demand manufacturing. Some retailers and brands have gathered lots of data about consumers. As a result, consumers will expect even more relevant and personalized experiences.
Manufacturers and retailers are also working to better educate shoppers to make returns less likely. AI can help to solve the difficult “what’s the right size” issue, so it’s less crucial to build more efficient reverse supply chains. Also here adding a special focus on the sustainability impact will be an increasing topic, brands and retails must pay attention.
To our speakers – Here a quick summary:
Frederic Kerber: What will the retail sector of the future look like? How can artificial intelligence help customers and employees in retail? The team of the Innovative Retail Laboratory (IRL) of the German Research Center for Artificial Intelligence (DFKI) is investigating these and other questions. Frederic briefly introduced the IRL and showed examples of its demonstrators that illustrate the practical applicability of artificial intelligence.
Christoph Schwerdtfeger talked about the challenges of deploying Deep Learning based applications to thousands of stores. He explains how to make the big step from impressive prototype to real products.
Christopher Gandrud focussed Fashion, the summation of aesthetic choices of individuals about what to wear. These choices are influenced by the social environment, including design, manufacturing, distribution, and marketing of fashion articles. Fashion presents considerable challenges for AI due to this complexity of topics and constantly changing fashion trends. These challenges drive AI forward. At the same time, AI has brought much to fashion and there is considerable potential to change even more. AI can improve what clothing options are available and accessible. Making it easier for people to find clothes that fit them well and that they feel great wearing and sharing. It can help reduce the environmental impact of fashion through more efficient manufacturing methods and optimised delivery. Christopher shared those benefits, many of which are already offered at Zalando, but also about how to be aware of the potential pitfalls of fashion AI and work to avoid them. For example, if implemented poorly, fashion AI could undermine data privacy or speed up unsustainable manufacturing practices.
Head of Innovative Retail Laboratory @ DFKI
Application-oriented AI research with the Innovative Retail Laboratory for the Retail of the Future
Preparing Deep Learning on edge devices for real scale
Head of Economics and Experimentation at Zalando
AI in Fashion: How each drives the other forward