Why representation in AI fashion matters
AI isn’t just about tech. It’s about who gets to shape the future. In this piece, we unpack how the fashion industry, long critiqued for lack of diversity, has a chance to reset using inclusive AI design, and why that matters for creators everywhere.
AI isn’t just about technology. It’s about who shapes the future — and whose stories get told.
As artificial intelligence transforms every corner of the fashion industry — from design to manufacturing to marketing — we face an urgent question: Will this new era correct past inequities, or repeat them?
The fashion world has long faced valid critique for its lack of diversity: in design leadership, on the runway, in cultural narratives, and in sizing. AI offers an opportunity to disrupt those patterns — but only if we are intentional about how we build, train, and apply it.
The Problem: Bias In, Bias Out
Many AI models today are trained on biased or limited datasets — often scraped from the internet, fashion lookbooks, Western-centric social media, and stock imagery that reflect narrow ideals of beauty, race, gender, and body type.
MIT Media Lab research has shown that AI facial analysis tools performed with 99% accuracy on white male faces, but dropped to as low as 65% for darker-skinned female faces (Buolamwini & Gebru, 2018).
The same risk exists in AI-generated fashion imagery. If trained on biased datasets, AI models can:
Reinforce Eurocentric beauty standards
Underrepresent plus-size bodies, disabled bodies, and gender-diverse identities
Flatten cultural richness into tokenistic stereotypes
Bias in data = bias in design. Without intervention, AI-driven fashion could entrench old inequalities under a shiny new surface.
The Opportunity: Building an Inclusive AI Fashion Ecosystem
Done right, AI can help the fashion industry become more diverse, more representative, more globally connected than ever before. Here’s how:
1️⃣ Inclusive Datasets = Inclusive Design
By curating diverse, global, inclusive training datasets, AI models can learn to:
Represent all skin tones, hair textures, body types, abilities, and genders
Draw from global fashion aesthetics — not just Euro-American trends
Honor cultural craftsmanship and local design languages
Meta’s Responsible AI team has published guidance on inclusive dataset building (Meta Responsible AI, 2022), and leading platforms like Stable Diffusion are now working to improve dataset transparency and balance (Stability AI, 2023).
2️⃣ Global Voices, Global Trends
Fashion is a global industry — but Western markets and aesthetics have long dominated. AI offers the potential to spotlight:
Designers and trends from Asia, Africa, Latin America, the Middle East
Indigenous design systems
Street style and youth-driven fashion subcultures worldwide
When trained on truly global visual data, AI can help democratize fashion trends — and amplify underrepresented voices.
3️⃣ Access: Lowering Barriers to Design
AI tools are opening doors for new creators, including:
Women — still underrepresented in leadership across fashion tech
BIPOC designers — who often face systemic barriers to entry
LGBTQ+ creators — who bring vital perspectives on identity, gender, and style
Disabled designers — for whom digital tools can create new pathways to participation
The World Economic Forum notes that AI has the potential to democratize creativity by lowering technical and financial barriers (WEF, 2023).
Why It Matters — Now
The AI fashion revolution is moving fast. According to McKinsey:
AI is already used by 28% of fashion brands in creative design processes (McKinsey State of Fashion Technology Report, 2023)
Adoption is forecast to reach 50% of brands by 2025
If we don’t address representation and bias now, we risk locking inequity into the very code that will drive fashion’s future.
The SHE IS AI Commitment
At SHE IS AI, we are committed to championing ethical, inclusive, human-centered AI in fashion.
Through initiatives like the AI Fashion Challenge, we aim to:
Promote AI tools and practices that uplift diverse voices
Spotlight underrepresented creators and perspectives
Encourage inclusive dataset development
Build an AI fashion ecosystem that truly belongs to everyone
This is not just about better technology — it’s about a better fashion future: one that celebrates the full spectrum of human creativity.
AI in fashion can be a force for inclusion, empowerment, and global creativity — but only if we actively build it that way.
Representation in AI fashion matters because fashion shapes culture — and AI is shaping fashion.
Now is the time to ensure that the next chapter of fashion is written by — and for — all of us.
Citations:
Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. MIT Media Lab.
Meta Responsible AI (2022). Building Inclusive AI.
Stability AI (2023). Stable Diffusion Responsible AI Commitments.
McKinsey (2023). State of Fashion Technology Report.
World Economic Forum (2023). AI and Creativity: How Emerging Tech Can Democratize Design.
