This article is part of the Future of AI, a collection of articles that investigates how artificial intelligence will impact the fashion and beauty industries in the years to come.
In Hangzhou, a shopper can ask an AI agent to assemble an entire wardrobe, try it on their virtual avatar, and purchase it all within the same super-app. Meanwhile, in Silicon Valley, startups are racing to build even more powerful large language models (LLMs) to compete with China. And in Brussels, lawmakers are debating how that same technology should be governed.
The AI race is a high-stakes geopolitical battle between governments competing to create the most powerful technology in order to increase their economic competitiveness and safeguard national security. But different countries have fundamentally different ideas about how AI should shape business and society. The gap between those ideas is where luxury brands now have to operate.
“We’re seeing multi-locality emerging, where because of deep AI and data use, there become more local specificities,” says Holger Harreis, senior partner at McKinsey. “These specificities differ by income segment and age around the globe, but they’re always present.”
Luxury executives are preparing to tackle this growing fragmentation. Rather than scaling a single AI strategy globally, experts say that brands will need to localize how they use AI and data market by market, applying AI selectively to enhance customer experience where it matters, while protecting the elements of luxury that must remain distinctly human. The result is not one AI-driven future for the luxury market, but several.
Different systems, different rules
Numerous governments — the US, China, France, the UK, Japan, the UAE, Saudi Arabia, Singapore, and more — have formally identified AI as central to their national, economic, and security strategies.
The most prominent players in the AI race are the US and China, bolstered by access to capital and driven by the growing geopolitical tensions between them. The US’s AI development is fast and startup-led. The key players — Nvidia, OpenAI, Google, Meta, Anthropic, Microsoft, and Amazon — are building models or tools, each with distinct strengths. “Maybe one is better at visualization, one is better at processing and coding, and one is better conversationally,” says Raakhi Agrawal, managing director and partner at Boston Consulting Group. “It’s more varied and containerized in the US.” This means brands must compete across multiple AI entry points simultaneously — from search to agents to platforms — potentially with no single dominant channel.
In China, companies including Deepseek, Moonshot, and Zhipu are building capable LLMs, but the AI landscape is largely being shaped by tech giants such as Alibaba and Tencent, who have access to vast amounts of consumer data from an ecosystem of integrated super-app platforms. “One platform can end up with a lot of customer data and know a lot about their preferences. But the more data and context that AI agents have, the better the recommendations are going to be and the more useful they are to a consumer,” Agrawal says.
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