Luxury’s Next Frontier: Battling for Visibility in the Age of AI with ChatGPT

Luxury’s Next Frontier: Battling for Visibility in the Age of AI with ChatGPT

As AI technology becomes a staple for luxury buyers, brands face a fresh challenge to capture consumer attention in the decision-making process, even before a specific brand or item is chosen.

What handbag should I buy for less than $4,000? Which brand of sneakers is the most fashionable or offers the best value for the money? These are two examples of questions that highlight one of the changes artificial intelligence is beginning to bring to the luxury shopping experience. Google, Instagram, the media, a distributor, and brand-owned and multi-brand stores continue to be part of the customer journey. But ChatGPT and other generative AI models can compile a ranked selection even before the consumer has visited a brand’s online store or sought advice from a salesperson.

The use of artificial intelligence to guide purchasing decisions is growing, particularly among high-spenders. Eighty-two percent of high-spending customers used some form of artificial intelligence during their most recent luxury purchase, compared to 28% among lower-spending buyers, according to the latest edition of *Luxe et Technologie*, produced by Bain & Company and the Comité Colbert.

Adoption varies, however, by market. Sixty-four percent of Chinese consumers included in the study used AI during their most recent luxury purchase, while the percentage stood at 54% in the United States. In France, it dropped to 27%.

Forty-seven percent of shoppers who ultimately purchased a product in-store reported using artificial intelligence during their shopping journey, confirming the growing influence of this technology on their decision to choose specific products or brands. While high-end fashion houses are still figuring out how to monetize AI, the technology is already present in the early stages of the decision-making process—when consumers are researching products, comparing alternatives, or narrowing down the number of options they will ultimately consider.

Artificial intelligence plays a decisive role in luxury purchases by high-spending customers

However, 70% of luxury-related searches analyzed by Bain and Comité Colbert do not mention any specific brand, and about 75% reflect an intent to discover or compare options. In these searches, the consumer does not have a specific brand in mind from the outset. Generative AI can determine which brands appear in the initial selection and which are excluded.

For example, searching for the price of a Chanel 2.55 is based on a specific choice that has already been made. Asking which luxury handbag to buy for less than 4,000 euros for everyday use leaves the proposed brand open. This difference, linked to guiding the decision-making process, shifts part of the competition to an earlier stage of the purchasing process—before the brand awareness a fashion house has built up translates into a visit to its website, a retailer, or a physical store.

The financial clout of the companies or groups behind these brands does not, however, guarantee the same level of presence in these responses. Among the thirty luxury brands with the highest visibility on generative search engines, 70% of the brands with more than €5 billion in revenue have a visibility share lower than their revenue share. All brands with less than €1 billion in revenue included in this ranking achieve visibility that is between three and eight times greater than their market share, according to the report. While the sample does not suggest an impending upheaval in the luxury hierarchy, it does introduce a variable that companies are gradually incorporating into their budgets.

In unbranded searches, external sources account for the majority of references used by models, according to the report. This implies that the origin of the information poses another challenge for brands. Thus, official websites account for only 10% of the sources cited in searches for watches and 45% for jewelry, according to the analysis conducted in collaboration with Meikai.

Companies with annual revenue of less than €1 billion achieve visibility that is three to eight times greater than their market share

Companies’ efforts are focused on the channels they directly control. Around 60% of luxury houses and groups are actively working on the content and structure of their own websites. Only 26% are taking action on external content, despite its significant impact on generative responses. This disconnect affects an industry that has invested for years in direct distribution, proprietary e-commerce, and control over customer relationships.

The pursuit of visibility on these engines has begun to be grouped under the term GEO, short for Generative Engine Optimization. The report notes that 48% of groups and fashion houses regularly monitor their performance in AI and GEO searches. Only 10% consider their current position to be strong, reflecting that the sector is still figuring out how to apply capabilities developed around traditional SEO or digital advertising to this new environment.

Google remains central to product and brand searches, as do social media, media outlets, retailers, and stores. AI adds an intermediary that organizes information before the consumer reaches those touchpoints. For the luxury sector, this layer matters because recommendations can begin even before a brand has been chosen.

A handbag priced under €4,000 might end up being purchased in a store, while high-end sneakers might be bought on a luxury e-commerce site. The list of options the customer carries with them may have been formed earlier. Therefore, making it onto that list is becoming a matter of visibility governed by different rules than those that for years dictated digital search—a space primarily dominated by Google.

This new challenge is falling to teams accustomed to managing traditional search engine rankings, who must now understand why a model prioritizes one brand over another in a generative response. Unlike SEO, the industry does not yet have established rules for measuring and optimizing that ranking.