Sales are increasing, but is authenticity disappearing? Heading into an era where "AI boosts clothing sales," how far will fashion growth strategies change?

AI makes fashion "faster, cheaper, and smarter." But is that enough?

The presence of AI in the fashion industry is rapidly increasing. However, the changes happening now are not about flashy future predictions. Instead, what's advancing on the ground is a very practical shift: reducing inventory misjudgments, minimizing unsold stock, speeding up promotions, and increasing the precision of customer service and searches. AI is becoming less of a "dream technology" and more of a practical tool to protect profit margins.

According to an analysis by UBS covered by WWD, the metric of annual sales divided by the number of employees in the fashion industry rose from $222,000 in 2017-2019 to $272,000 in 2021-2025. Of course, attributing all this improvement to AI would be an overstatement. However, UBS believes that the adoption of AI within the industry is progressing faster than expected, and its effects are already starting to show in the numbers. In another UBS benchmark, 96% of the 45 companies surveyed were utilizing AI. This indicates that the fashion industry has almost moved past the stage of debating "whether to use AI" and has entered a phase of competing on "where and how much results can be achieved."

The acceleration of this trend is driven by the industry's unique struggles. McKinsey anticipates low growth for the fashion market in 2026, and amidst ongoing tariffs, rising costs, and cautious consumer behavior, AI is becoming less of a competitive advantage and more of a "business continuity necessity." In the survey, over 35% of executives were already using generative AI for online customer service, image creation, copywriting, and product exploration. Despite the glamorous appearance of the industry, there is increasing pressure internally to "do more with fewer people."

AI is most evidently effective in improving sales methods. Deciding who to show what, in what order to propose, and which products can be sold out without discounts. If the accuracy of these decisions improves, it can alleviate the chronic issue of heavy discounting that has long plagued fashion companies. UBS also sees AI-driven demand forecasting and hyper-personalization as directly contributing to improved profit margins. In other words, AI is playing a role in gradually adjusting the business model reliant on discounts before it becomes a substitute for creativity.

Consumer behavior is also beginning to change. According to Adobe, traffic to U.S. retail sites via generative AI increased by 4,700% in July 2025 compared to the same month the previous year. Among survey respondents, 38% had used generative AI for online shopping, and 85% reported an improved shopping experience. Visitors via AI stayed 32% longer and viewed more pages. Essentially, consumers are starting to use AI not as a "search substitute" but as a "shopping consultant." For fashion companies, it's no longer enough to just focus on Google optimization; they now need to design how they are found and talked about by AI.

Looking further ahead, a world where AI agents take the lead in shopping is also emerging. BCG points out the advancement of "agentic commerce," where AI shopping agents handle product exploration, comparison, recommendation, and purchase, warning of the risk of brands losing direct contact with customers. If scenarios where price, reviews, delivery speed, and inventory immediacy take precedence over the brand's cherished worldviews and loyalty increase, fashion may shift more towards "optimization" than "aspiration." As efficiency progresses, it may become even harder to protect a brand's individuality.

However, the benefits of AI are not limited to marketing and search. In the fields of size recommendation and virtual fitting, practical benefits such as improved return rates are starting to emerge. Zalando explained that in a small-scale pilot conducted with Levi's and others, the return rate in the jeans category decreased by up to 40%. Size mismatches are one of the biggest wastes in fashion in the e-commerce era. If this can be reduced, AI could potentially impact not only sales but also costs and environmental burden.

However, the sentiment on social media is not one of unreserved welcome. Public posts reveal reactions that are largely divided into two. One is the practical welcome group, saying "AI has finally moved beyond the experimental stage into everyday operations." On LinkedIn, comments can be seen to the effect that AI is no longer just a buzzword but a part of "everyday ops." There is indeed strong support for the positive view of efficiency, inventory optimization, customer service automation, and faster trend recognition.

The other is the cautious voice asking, "Even if it's convenient, what might be lost beyond that?" A particularly common concern is that using AI with biased size and body data could expand existing biases. Public comments also pointed out that while AI's size recommendations are convenient, if the learning data is biased, it could reproduce problems on a larger scale. Additionally, there is a strong concern that as AI can instantly generate a large number of images and product suggestions, the aesthetic sense of each brand may diminish, leading to an increase in similar appearances.

This "anxiety" is most strongly erupting in the realm of advertising visuals. According to Vogue, Aerie announced a policy in October 2025 to "not use AI-generated bodies or people in advertisements," and their subsequent Instagram rollout was widely disseminated. In the Pamela Anderson campaign in March 2026, they further clarified this stance, reporting double-digit growth in brand recognition and a 23% increase in sales in the fourth quarter of 2025. In other words, on social media, not only are "brands that use AI" gaining attention, but "brands that deliberately do not use AI" are also strongly supported.

This phenomenon is not unique to Aerie. The Wall Street Journal reported that amidst the overflow of AI-generated content, brands are beginning to use "No AI" labels for differentiation. As consumers become less inclined to trust images and videos online as they once did, "being made by humans" itself is becoming a value in both luxury and mass markets. Fashion is originally an industry that sells stories. Therefore, the more efficiency is increased with AI, the heavier the question "Is this real?" becomes than before.

In the end, AI strengthens the fashion industry. At least in the short to medium term, the potential is high. Planning becomes faster, customer service becomes smarter, returns decrease, and inventory becomes lighter. However, what AI creates is a "system that sells easily," not the "reason to fall in love with it" itself. What ultimately differentiates a brand is its worldview, values, physical sensations, and the emotions that make people want to wear the clothes. In an era where AI becomes the foundation of the industry, fashion paradoxically requires the power to fully express human qualities. Convenience alone does not create enthusiasm.

*The SNS reaction part is a summary of trends in posts and comments on LinkedIn, Instagram, and X that could be confirmed in a public state, and is not a statistical survey.