Generative AI for fashion industry

K Raveendran
Generative AI has been described as a milestone that will be as impactful as the advent of internet. The optimism is matched by an equal measure of concern over its effect on employment as also ethical questions about its use, apart from its potential for mischief. But according to a new analysis, while still nascent, generative AI could add up to $275 billion to the apparel, fashion, and luxury sectors’ operating profits in the next three to five years alone.
The analysis by McKinsey partners Holger Harreis, Theodora Koullias, Roger Roberts, and Kimberly Te, assert that generative AI has the potential to help fashion businesses become more productive, get to market faster, and serve customers better.
OpenAI’s ChatGPT became an overnight sensation and sparked a digital race to build and release competitors. It became available only recently and still has bugs and other worries to be addressed. ChatGPT is only one consumer-friendly example of generative AI, a technology comprising algorithms that can be used to create new content, including audio, code, images, text, simulations, and videos. Rather than simply identifying and classifying information, generative AI creates new information by leveraging foundation models, which are deep learning models that can handle multiple complex tasks at the same time.
From codesigning to speeding content development processes, generative AI creates new space for creativity. It can input all forms of “unstructured” data-raw text, images, and video-and output new forms of media, ranging from fully-written scripts to 3-D designs and realistic virtual models for video campaigns.
The authors say generative AI is not just automation; it is rather about augmentation and acceleration. That means giving fashion professionals and creatives the technological tools to do certain tasks dramatically faster, freeing them up to spend more of their time doing things that only humans can do. It also means creating systems to serve customers better. Fashion companies can use the technology to help create better-selling designs, reduce marketing costs, hyperpersonalize customer communications, and speed up processes. It may also reshape supply chain and logistics, store operations, and organization and support function.
Using tools from tech companies such as Cala, Designovel, and Fashable, fashion designers are already tapping into the power of generative AI to spark new ideas, try myriad design variations without having to produce expensive samples, and vastly accelerate their processes. In December 2022, a group of Hong Kong-based fashion designers from the Laboratory for Artificial Intelligence in Design (AiDLab) held a fashion show featuring generative-AI-supported designs.
According to McKinsey research, generative AI could also be applied to personalized customer communications. The findings suggest that companies that excel at personalization increase revenues by 40 percent compared with companies that don’t leverage personalization. Several start-ups are already helping pioneer personalized marketing at scale through generative AI, the tools for which offer several options from which the marketer can choose.
Generative-AI-powered chats, which use stronger natural-language processing to better understand and interact with humans, are already a measurable improvement over existing AI chats. Yet, current chatbots and other text-generating tools still occasionally make errors that could cause serious customer service disasters. Eventually, though, this technology could help customer support agents outsource complex inquiries-for example, using chatbots to help provide personalized responses in numerous languages. A generative AI ‘representative’ can handle customer service queries across email, chat, text, and a brand’s own platforms. These services help to reduce customer service wait times and improve response times.
Virtual try-ons are yet another example of how generative AI can improve sales and consumer experience. Paris-based Veesual enables virtual try-on integration for e-commerce fashion brands, meaning customers can choose their model and pick clothes to try on.
The McKinsey analysts point out that even as generative-AI technology is exciting, companies will still want to tread cautiously before entrusting any of their core tasks entirely to generative AI. But neglecting to explore the possibilities that this technology offers could be just as risky, given the pace at which it is evolving and the explosive growth of the user base. (IPA)