The Fashion AEO Report: Q2 2026
The top 5 insights on how AI search engines are reshaping discovery for premium contemporary fashion brands.
- 62% of all fashion brands cited appeared exactly once. Of 860 unique brands surfaced, 530 showed up in one model, for one prompt, then vanished.
- Who What Wear cites fashion brands more than 6x as often as Vogue. 93 mentions across 38 of 50 prompts vs Vogue at 15. The assumed industry authority is not the actual citation engine.
- AI fashion search is four markets, not one. Everlane wins category and need-based discovery. Reformation wins values-led discovery. Khaite and Toteme win editorial authority. Different rules, different winners.
- 19 of 50 prompts return a completely different top brand on each of the four models. Brands auditing AI visibility on a single model are not getting a partial picture, they are getting a misleading one.
- Wikipedia drives 38 of 41 citations on ChatGPT alone. Other models barely touch it. Brand Wikipedia presence is structurally required for ChatGPT visibility and irrelevant elsewhere.
What's inside
We ran 50 unbranded prompts across ChatGPT, Gemini, Perplexity and Claude, simulating how a US premium contemporary buyer actually uses AI search. The dataset covers 2,423 brand citations, 860 unique brands and 1,324 source URLs across four intent layers: category discovery, need-based discovery, attribute-based discovery, and editorial authority.
The report breaks down the overall leaderboard, the four sub-leaderboards with different winners, the citation engine that decides who gets surfaced, and the per-model dynamics that mean a single-model audit will mislead you. It also includes the specific URLs the AI models actually cite, so PR and content teams know exactly which pages to target.
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