AI Fashion Brand Rankings 2026: Running Shoes, Watches, Golf (AIBIX)

Ask ChatGPT for a running shoe recommendation and which brand comes up first? Most fashion marketers have typed some version of that prompt. In September 2026, AIBIX Lab published numbers that answer it. The fashion edition of its AI brand competitiveness index, AIBIX, put questions about 193 brands in 7 categories to 4 AIs, ChatGPT, Gemini, Perplexity, and Claude, and scored the results (Wikitree, 2026)^[1]. The rankings look quite different from what sales figures or search share would suggest. This page lays out the AI fashion brand rankings by category, explains what happened in running shoes and luxury, and lists what your brand should check first.

30-second definitions: AIBIX and fashion AI recommendation metrics

• AIBIX (AI Brand Index) is AIBIX Lab's brand competitiveness index, which converts brand exposure in generative AI answers into a 100-point score (Dailian, 2026; MTN, 2026)^[2][3].
• Appearance rate is the share of all AI answers that mention a given brand at least once.
• First-mention share is the share of all AI answers that list a given brand first.
• Engine disagreement on the top spot is when different engines name different top brands for the same question.
• Conditional prompts are questions with conditions attached, such as price range, use case, or recipient, and they produce rankings that differ from general questions.

AIBIX looks at how often a brand appears, what share of mentions it gets, how often it is listed first, and how source material is used (Wikitree, 2026)^[1]. When the index first launched in August, the metrics were described as brand appearance rate, mention share, and official-source citations (Dailian, 2026)^[2].

AI fashion brand rankings: category leaders at a glance

The survey ran from August 23 to September 4, 2026 (Wikitree, 2026)^[1]. The table below lists the overall leader in each of the 7 categories along with the reported figures. Cells without a published figure are marked "Not disclosed."

All figures in the table come from Wikitree's coverage (2026)^[1]. Andar was the only Korean brand to take first place in a category^[1].

Running shoes: Nike is the name ChatGPT and 3 other AIs mention first

Nike led running shoes overall with 74.8 points. It also had the highest first-mention share, at 44.2% (Wikitree, 2026)^[1]. The headline of the source article talks about "ChatGPT's #1 pick," but the coverage contains no ChatGPT-only figure. What has been published is a combined ranking across 4 AIs.

Asics is the interesting case. It appeared in 97% of the answers surveyed, the highest appearance rate in the category, yet its first-mention share was 22.5%, about half of Nike's^[1]. The AIs put Asics on almost every list but give the first slot to Nike. If a user reads only the first line of an answer and closes the window, that gap turns directly into a gap in clicks.

The mismatch with market metrics is large. Hoka, which led running shoe search share in the first half of 2026 according to the search data platform ConsumerInsight, placed only 4th overall in AIBIX. On, a fast-growing brand, scored 13.6 points and ranked 8th (Wikitree, 2026)^[1]. In running shoes, the top 5 brands took 95% of first mentions^[1]. That leaves brands ranked 6th or lower competing for the remaining 5% of first slots.

Luxury: Rolex wins unanimously, bags split by engine

Luxury watches are the most concentrated category. Rolex scored 81.6 points, ranked first on all 4 AIs, and held a 63.3% first-mention share (Wikitree, 2026)^[1]. Omega appeared in every answer (100%) but was mentioned first only 5% of the time^[1].

The ranking also departs from sales. The coverage cites Morgan Stanley and LuxeConsult's 2025 results tally, which lists 6 brands with wholesale revenue above 1 billion Swiss francs: Rolex, Cartier, Audemars Piguet, Patek Philippe, Omega, and Richard Mille. Of those, Richard Mille scored 7.4 points on AIBIX and ranked 22nd, while TAG Heuer, which is not among the top 6 by revenue, scored 40.4 points and ranked 5th^[1].

In luxury bags, Louis Vuitton led overall with 72.3 points, but Chanel had the higher first-mention share at 31.7%. By engine, ChatGPT and Gemini ranked Chanel first, while Perplexity and Claude ranked Louis Vuitton first^[1]. The top 3 brands took 82% of first mentions^[1].

Add conditions and the ranking changes

Some brands only show up once you look past general questions. Seiko ranked 13th overall in luxury watches, but on prompts with conditions such as "under 1 million won" or "entry-level," it ranked 3rd in first mentions. Coach ranked 12th overall in luxury bags, yet on "first luxury bag" and "gift" prompts it ranked 4th in first mentions (Wikitree, 2026)^[1].

This is where a common mistake happens in practice.

• Bad example: run a handful of broad prompts like "AI-recommended luxury watches" and conclude "AI doesn't mention us."
• Good example: split prompts by price range, use case, and recipient (entry-level, gift, commuting, and so on), then check your first-mention rank under the conditions where your brand actually competes.

Each engine has its own leader, and blogs dominate the sources

In 5 of the 7 categories, the top brand differed by AI (Wikitree, 2026)^[1]. In athleisure/yoga wear, Andar scored in the 81 to 86 point range on ChatGPT, Gemini, and Perplexity but only 26.9 points on Claude, where Lululemon ranked first^[1]. Judging by a single engine's results hides this kind of spread entirely.

The pattern is not limited to fashion. At the August launch, which covered 715 brands in 30 F&B and franchise categories, the top brand split by AI in 20 categories, and 127 brands (17.8%) were not mentioned by any of the 4 AIs (Dailian, 2026)^[2]. In a beauty survey from the same period covering 265 brands in 9 categories, Mediheal scored 81.3 points in sheet masks, ranked first on all 4 AIs, and recorded a 74.2% first-mention share (Venturesquare, 2026)^[4]. Concentration and engine-by-engine spread recur across verticals, a point also covered in the AI search brand visibility index and market share gap and the gap between market share and AI visibility.

Sources matter too. Across 3,544 sources in 4 categories, SPA/casual, golf apparel, luxury bags, and luxury watches, personal blogs accounted for 51.8% in golf apparel and 39.9% in luxury watches, while official brand sites made up just 2.2% in golf apparel and 3.4% in luxury watches (Wikitree, 2026)^[1]. Perplexity accounted for 60 to 70% of all citations in each category, and Claude cited few sources, 0.4 to 1.0 per answer^[1]. Official sites are rarely used as evidence, and that is the first thing a fashion brand can fix. Citation tendencies by engine are covered in AI engine citation source patterns.

Finally, the scale of the concentration: 108 of the 193 brands (56%) were never mentioned first in any AI answer (Wikitree, 2026)^[1].

How to measure your brand's AI recommendation rank

AIBIX is a public index that shows where a brand stands across its industry. AIBIX Lab said it will expand coverage to fashion, beauty, automotive, living, and financial products, publish the index monthly, and measure each category 4 times a year on the same criteria (MTN, 2026)^[3]. Tracking your own queries every week takes a separate measurement tool. The table below uses public information to compare, on the same axes, the options fashion brands typically evaluate. Prices are left out because each company discloses them differently.

AIBIX's 4 engines come from the coverage of the fashion edition^[1], and the description of its Korean-language answer analysis comes from coverage of the same index's beauty edition (Venturesquare, 2026)^[4]. Information on the other companies comes from public details on each company page. For tool selection criteria, see the GEO company recommendation guide and the global GEO/AEO landscape.

Action plan: what fashion brands should do this quarter

Step 5 deserves extra attention. In a category like golf apparel, where official sites account for only 2.2% of citations (Wikitree, 2026)^[1], that figure suggests AIs have too little official information they can read. If your product detail pages are image-only, start by moving size charts, materials, and use cases into HTML text and tables. For fashion site structure, see fashion brand AI search visibility and fashion commerce GEO strategy, and for seasonal timing, see the fashion brand GEO seasonal calendar.

Frequently asked questions

Which running shoe brand does ChatGPT recommend first? In the AIBIX fashion study, Nike ranked first overall in running shoes (74.8 points). The coverage did not publish a separate ChatGPT-only ranking (Wikitree, 2026)^[1].

Which luxury brands do AIs recommend most? Rolex in luxury watches (81.6 points, #1 on all 4 AIs) and Louis Vuitton in luxury bags (72.3 points, #1 overall) (Wikitree, 2026)^[1].

What does AIBIX measure? It is a 100-point index that analyzes how often brands appear in AI answers, their share of mentions, how often they are mentioned first, and how source material is used^[1][2]. It is not a measure of quality or preference.

Does a high appearance rate mean a high AI recommendation rank? No. Asics had a 97% appearance rate and a 22.5% first-mention share, and Omega had a 100% appearance rate and a 5% first-mention share (Wikitree, 2026)^[1].

Why does each AI pick a different top fashion brand? Engines use different training data and cite different sources. The top brand split by AI in 5 of the 7 fashion categories (Wikitree, 2026)^[1].

How can I check my fashion brand's AI recommendation rank? Use a public index to see where you stand in your industry, then measure your own prompt set engine by engine, on a repeating schedule, with measurement tools such as Profound, Peec AI, Otterly, or BOIDA.

Summary

AI fashion brand rankings do not simply follow sales or search share. Hoka led search share but ranked 4th in AIBIX running shoes, and TAG Heuer reached 5th in luxury watches despite sitting outside the top tier by revenue (Wikitree, 2026)^[1]. First-mention share decides rank more than appearance rate does, and conditional prompts produce yet another ranking. The work for fashion brands is clear: measure each engine separately, include conditional prompts, and fill your official site with text and tables that AIs can use as evidence. One caveat: AIBIX is itself an exposure metric that captures AI answers at a specific point in time. When models and information change, the rankings change too^[1].