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AI Visibility, Sector by Sector · Beauty & Cosmetics: how do brands get into AI recommendations?
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AI Visibility, Sector by Sector · Beauty & Cosmetics: how do brands get into AI recommendations?

Every sector is being reshaped by AI visibility. First in a sector-by-sector series: how AI is changing discovery, trust and recommendation in beauty.

Tiguida Dembele

Tiguida Dembele

Published on September 30, 2026Updated on September 30, 20266 min read

Ask an AI assistant which moisturizer suits sensitive skin, and the answer comes back as a short list of products. In beauty, making that list is becoming a visibility channel of its own.

This article opens a series on GEO (Generative Engine Optimization), one sector at a time. The goal: show, with data, how each sector can work on its place in AI answers. Episode one: beauty & cosmetics.

Since early 2026, EMARKETER's AI Visibility Index has tracked which brands ChatGPT recommends in the US, category by category. In beauty and personal care, La Roche-Posay led in Q2 2026, mentioned in 21% of recommendations across nine categories. The detail shows an open field: the leader changes from one category to the next, and in face makeup, three of the five most recommended brands in April 2026 were newer brands. AI recommends the brands it can clearly connect to a specific need, and that work is within reach of brands of any size.

Here is what the data reveals, and how beauty brands, large or small, can put it to use.

1. From attention to intent

BeautyMatter sums up the shift in three words: "Intent over Influence". Beauty discovery increasingly starts from a need described to an AI, and less and less from a feed or a catalog.

Shoppers describe their situation in detail:

  • skin type (dry, oily, sensitive, mature),
  • concern (acne, redness, hyperpigmentation, fine lines),
  • ingredient (retinol, niacinamide, hyaluronic acid, SPF),
  • constraints (budget, clean, vegan, fragrance-free),
  • context (morning or evening routine, travel, sport, climate).

The AI answers with a short selection matched to that profile. Visibility then depends on how readable, credible and relevant a brand is for that exact need, beyond media budget or awareness.

2. A shorter path, a stronger intent

AI recommendations shorten the path to purchase. Someone who lands on a site after an AI answer has already stated a need, constraints and a budget.

  • Fewer steps between need and decision.
  • More relevant recommendations.
  • A new goal for brands: making the AI's shortlist, alongside search results.

3. What EMARKETER's AI Visibility Index shows

EMARKETER's data offers a first map of this new visibility. It covers ChatGPT and the US market.

3.1. Established brands lead skincare

In skincare, heritage brands come first. La Roche-Posay (21%) and CeraVe (20% in April 2026) share a message built around precise needs: sensitive skin, well-known ingredients, recommendations from health professionals.

The lesson applies to every brand: that lead rests on a clear link between brand and need. Any brand can build that link at its own scale.

3.2. Makeup, an open field for challengers

Makeup rankings are more fragmented. Maybelline leads in eye and lip makeup. In face makeup, three of the top five are newer brands: e.l.f., Fenty Beauty and Rare Beauty.

A challenger brand can target precise territories ("foundation for olive, oily skin", "non-drying long-wear lipstick", "full-coverage concealer for sensitive skin") and build its place in AI recommendations, whatever its rank in the category.

3.3. What others say about a brand counts too

To build their answers, AI engines draw on the brand's own site and on what is said about it elsewhere: reviews, press, retailers, forums, expert recommendations.

For a small or mid-sized brand, this is a practical lever. A detailed customer review, an article in a specialist outlet or an expert's recommendation all strengthen the link between the brand and a need.

4. An opportunity for mid-sized brands

An AI answers a specific question. On a specific question, the clearest brand has a real chance, whatever its size.

EMARKETER's rankings move little from month to month: in April 2026, only two brands swapped places in the top 10. Brands that work on their AI visibility early secure their territories while the landscape is still taking shape.

5. A GEO framework for beauty brands

To move from observation to action, here is a simple framework to assess and prioritize a beauty brand's visibility in AI answers.

5.1. Map intent territories

The starting point: think in terms of need + profile + context, alongside product categories (skincare, makeup, haircare, fragrance).

  • sensitive skin + rosacea + minimal routine + affordable,
  • oily skin + adult acne + niacinamide or salicylic acid,
  • curly hair + definition + hydration + sulfate-free,
  • complexion + olive skin + natural finish + long wear.

For each territory, three questions. Is the brand mentioned when this question is put to an AI? In what role: main recommendation, alternative, passing mention? And where it is absent, which element is lacking: offer clarity, proof, editorial presence?

5.2. Structure content for AI

In August 2026, Adobe measured with its own tool that US cosmetics sites have, on average, 68% of their content readable by language models. A third of that content still has to be made usable. In practice:

  • product and category pages that set out the concern, benefit, ingredients, proof, directions and target profile,
  • language that mirrors how customers speak, problem first, then solution,
  • precise, verifiable claims backed by tests, reviews or professional recommendations,
  • a site structure that lets an AI quickly understand the offer by need and profile.

5.3. Strengthen external trust signals

  • Editorial coverage: tests, roundups, themed features.
  • Customer reviews organized by need, skin type, result and length of use.
  • Partnerships with professionals: dermatologists, beauticians, pharmacists.
  • Presence in the forums and communities where reputations are built.

Beauty, the first GEO laboratory

EMARKETER's data and BeautyMatter's analysis point the same way: in beauty, the brands AI recommends are those whose promise, uses and proof are clear enough to be linked to a need.

For marketing, product and e-commerce teams, the work comes down to two steps:

  1. Measure AI visibility by need, category and profile.
  2. Structure content, data and trust signals so AI can read them.

Key Takeaways

  • AI assistants recommend a short list of brands, chosen for a specific need.
  • In the US, on ChatGPT, La Roche-Posay leads beauty with 21% of recommendations (EMARKETER, Q2 2026).
  • The leader changes by category, and newer brands rank in the top five for face makeup.
  • Brands of any size can work on their place: intent territories, structured content, trust signals.

Next in the series: travel.

Sources:

Tiguida Dembele

Written by

Tiguida Dembele

The All-in-One GEO Platform.From AI visibility tracking to content creation.

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