We’re in a Gilded Age of fast, cheap, and trendy clothing. Anyone can purchase copies of expensive garments online that arrive at record speeds to their home, and for a fraction of the original price. This practice has made items affordable — often at the expense of the workers making the products — and created shopping habits that can be wasteful and impulsive. One e-comm giant, Shopify, estimates that 20 to 30 percent of online purchases are returned, while the National Retail Federation says around 18 percent of online orders are returned.
The online fashion house, Finesse, is promising to change that. Their motives are to reduce overproduction by using AI to market and design their clothing exactly for their audience.
Retailers have embraced generative AI: eBay sellers can auto-generate product descriptions, Amazon promises its AI fit feature will help you find the right size for clothing, and Shopify has rolled out AI tools to edit images and write website copy. Levi’s even experimented with AI models in order to “increase diversity” without actually hiring diverse models (unsurprisingly, customers weren’t thrilled).
But can AI actually help improve the online shopping experience? In this episode of Status Update, Verge reporter Mia Sato explores how the retail landscape has changed with the use of AI and what purchasing an AI-designed wardrobe is actually like.
Posted from: this blog via Microsoft Power Automate.
0 Comments