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Vicky Beercock

Creative Brand Communications and Marketing Leader | Driving Cultural Relevance & Meaningful Impact | Collaborations

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👗 The AI Supermodel in Vogue: Fashion’s Beauty Standard Crisis

This month, for the first time in its history, Vogue featured an AI-generated model in a Guess advert. At first glance, she looks like many models before her - tall, slim, blonde, blue-eyed, flawless. But she is not real. The image was created entirely by an AI studio, and the move has sparked fierce criticism for reinforcing unrealistic beauty ideals, undermining diversity gains in fashion, and potentially harming the mental health of young audiences. For brands, it raises urgent questions about representation, transparency, and the ethics of innovation.

Supporting Stats

  • 88% of women and girls say they compare themselves to images they see in the media, with more than half describing the comparison as negative (Dove Self-Esteem Project, 2024).

  • In the UK, one in three teenage girls report poor body image, a risk factor for eating disorders (Beat, 2024).

  • Research shows AI beauty bias mirrors historic human bias - when asked to generate “the most beautiful woman in the world”, AI tools overwhelmingly produce images of white, slim, young women with Eurocentric features (Dove Campaign, 2024).

Pros - Why Brands Are Experimenting

  • Innovation appeal: AI-generated models position a brand as tech-forward and experimental.

  • Cost efficiencies: No travel, styling, or location fees; scalable across campaigns.

  • Creative control: Every pixel can be shaped to match brand vision without the unpredictability of live shoots.

Cons - What’s at Stake

  • Reinforcing harmful beauty ideals: AI models can deepen exclusion by defaulting to narrow, Eurocentric standards.

  • Loss of authenticity: Fashion thrives on human individuality and cultural resonance - synthetic perfection risks alienating audiences.

  • Job displacement: From models to makeup artists, AI threatens established roles across the creative supply chain.

Opportunities - Doing It Differently

  • Inclusive AI training: Brands could actively train AI on diverse datasets representing all body types, ethnicities, ages, and abilities.

  • Personalised fashion tech: Using AI to create avatars of real customers could democratise the model experience and help consumers see themselves in products.

  • Creative partnerships: Collaborating with artists, activists, and models to co-create AI visuals grounded in real-world representation.

Challenges - The Risks to Manage

  • Transparency gaps: UK law does not require clear labelling of AI-generated content, leaving room for misleading advertising.

  • Audience backlash: As seen with Guess and Vogue, poorly executed AI campaigns can trigger reputational damage.

  • Mental health implications: Hyper-perfect, non-human images risk fuelling body image anxiety, particularly among young audiences.

Key Takeouts

  • AI fashion models are no longer a futuristic novelty - they are here, and they influence beauty culture now.

  • Without conscious bias mitigation, AI will replicate and amplify exclusionary beauty standards.

  • Transparency is essential. If audiences cannot easily tell what is real, trust erodes.

  • Brands risk reputational harm if innovation is perceived as cost-cutting at the expense of representation.

Next Steps for Brand Marketers

  • Audit AI usage: If using AI-generated imagery, review datasets for diversity and inclusivity.

  • Label clearly: Make AI origins visible and readable - not hidden in fine print.

  • Engage communities: Involve real voices in shaping how AI represents people.

  • Balance innovation with impact: Don’t adopt AI in a way that undermines your brand’s values or alienates audiences.

  • Track sentiment: Monitor audience reaction and be prepared to adjust campaigns quickly if backlash emerges.

categories: Tech, Fashion
Friday 08.01.25
Posted by Vicky Beercock
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