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How AI Fashion Brands Are Shaping the Fabric of Fashion

Ian Anderson2025-05-28

By 2025, artificial intelligence (AI) has moved from the sidelines of tech conferences to the front rows of fashion week. No longer confined to chatbots or backend analytics, AI now drives creativity, personalizes style experiences, and enhances operational efficiency in the fashion world.

With the US fashion industry estimated to cross $500 billion by 2025, brands are under pressure to deliver faster, greener, and more intelligently designed clothing. AI isn’t just a nice-to-have anymore—it’s the core differentiator. And the brands leading this revolution are combining art and algorithms in ways never imagined before.

Let’s explore how AI fashion brands are transforming the fashion value chain—from the sketchbook to the shopping cart—and spotlight the most forward-looking US fashion brands embracing this transformation.

AI Fashion Brands Transforming Fashion at Every Level

ai fashion

1. AI in Product Design: From Data to Dresses

Designers are increasingly using AI tools in retail that analyze runway trends, social media aesthetics, and even weather patterns to inform their creative process. Instead of relying solely on intuition or legacy data, AI helps predict what consumers will want to wear next season—and why.

Example: Tommy Hilfiger, in collaboration with IBM and the Fashion Institute of Technology, launched an AI design project using insights from thousands of data sources to inform collection creation. This enhanced, not replaced, the creative vision.

2. Hyper-Personalization: The New Luxury

In an era of infinite choice, relevance becomes the ultimate luxury. AI fashion brands that can anticipate customer needs gain a significant edge in loyalty and conversion.

Example: Stitch Fix uses AI-powered recommendation engines built on millions of data points. Nike’s Fit App scans a user’s foot via smartphone to recommend the perfect shoe size, eliminating return-related frustrations.

3. Smart Supply Chains: Fast, But Sustainable

Fast fashion’s biggest flaw has been its environmental impact. AI is helping brands address this by optimizing inventory, reducing overproduction, and improving demand forecasting.

Zara, the pioneer of fast fashion, now uses AI to monitor store-level data, social media mentions, and local weather patterns to decide what clothes to manufacture, and where to ship them. This micro-level intelligence allows them to stay fast and reduce waste.

Ralph Lauren has also integrated AI to better manage in-store inventory and sales, improving sell-through rates while minimizing markdowns.

4. Sustainable by Design

As sustainability becomes non-negotiable, AI fashion brands are using predictive analytics to improve recyclability and reduce waste.

Example: H&M uses AI to sort used garments and predict fabric lifespan, enabling more informed circular design practices.

The Rise of Digital Fashion and Immersive Experiences

Beyond the physical, AI fashion brands are pioneering the digital realm.

  • Virtual Try-ons and Augmented Reality (AR): AI powers highly realistic virtual try-on experiences, allowing customers to see how clothes fit and look on their own bodies or customizable avatars from anywhere, significantly reducing returns and enhancing online shopping.
  • Virtual Clothing and NFTs: Brands are creating digital-only clothing for avatars in metaverses and gaming platforms. Non-fungible tokens (NFTs) are being used for exclusive digital collectibles, or even linked to physical garments for enhanced authenticity and traceability. This opens up new revenue streams and forms of self-expression.

AI-Generated Models and Content: AI fashion brands are increasingly utilizing AI-generated virtual influencers and models for marketing campaigns, offering diverse representations without the need for traditional photoshoots, streamlining content creation.

10 Most AI-Forward Fashion Brands (2025 Edition) 

Brand

AI Application Area

Purpose / Outcome

Example/Outcome Details

J.Crew

Customer Data Platform, ML-driven analytics

Same as above (J.Crew Factory and J.Crew share tech stack and use cases)

Uses Acquia CDP for deduplication, segmentation, campaign activation, daily customer scoring, and reporting

US Polo Assn.

AI/ML-driven customer profiling, marketing

Precise targeting, personalized offers, increased sales and ROI

AI profiles customers, targets across channels, and drives significant campaign results.

American Eagle Outfitters

AI-based inventory management, personalization

Accurate inventory, reduced excess stock, personalized online shopping

AI tools for inventory, warehouse automation, and hyper-personalized recommendations.

Calvin Klein

Predictive analytics, recommendation engines

Trend forecasting, product suggestions, marketing personalization

AI analyzes trends, powers smart mirrors, and delivers inventory optimization.

Banana Republic & Old Navy (Gap Inc.)

AI-driven productivity, trend forecasting, inventory optimization

Enhance consumer experience, improve product development, optimize inventory

Dedicated AI unit for customer experience and digital-first operations.

Madewell US

Digital transformation, AI for customer support

Seamless shopping, loyalty program enhancements

Mobile app and loyalty innovation; industry-standard AI for digital support.

7 For All Mankind

AI-powered sizing technology

Reduce returns, improve customer satisfaction

Uses MySizeID for AI-driven fit recommendations.

Carhartt

AI for merchandising and marketing

Predict consumer needs, personalize content, optimize inventory

AI analyzes data for inventory and marketing automation.

Diane von Furstenberg

AI-powered personalization

Tailored e-commerce experiences, higher engagement and conversion

Qubit ML for real-time offers, personalized recommendations, and mobile relevance.

Banana Republic Factory

AI-powered loyalty, chatbots, proximity messaging

Enhance in-store and loyalty experiences, drive store visits

Uses flok platform for AI chat, rewards, and geofencing.

How Glance AI is Contributing in Making AI Fashion Brands More Powerful

Glance AI plays an important backend role in enhancing how fashion brands engage with their customers. With partnerships with labels like U.S. Polo Assn.Levi’s, and American Eagle, Glance helps surface personalized fashion content and recommendations directly on smartphone lock screens—bridging the gap between brand and buyer in micro-moments. 

With its multi-screen strategy, Glance is expanding this discovery across connected devices—from mobile phones to smart TVs—offering a seamless, omnichannel fashion journey. Through partnerships with brands like U.S. Polo Assn., Levi’s, and American Eagle, it delivers curated looks based on user preferences and trends.

Moreover, the concept of an AI twin—a virtual assistant that learns a shopper’s taste and helps them experiment with styles—is gradually being integrated,  empowering you to make smarter, bolder fashion choices, all while enhancing convenience and engagement. 

Ethical Considerations and the Future of AI in Fashion

While the benefits of AI are undeniable, the rise of AI fashion brands also brings crucial ethical considerations:

  • Data Privacy and Security: The vast amounts of personal data collected by AI systems raise concerns about privacy. AI fashion brands must ensure robust data protection measures and transparent data usage policies to maintain consumer trust.
  • Bias in AI: AI algorithms learn from historical data, which can sometimes reflect societal biases. This could lead to biased recommendations (e.g., favoring certain body types or demographics) or perpetuate stereotypes. Ensuring diverse and inclusive datasets is vital to mitigate this.
  • Intellectual Property: With generative AI creating novel designs, questions of intellectual property ownership and copyright become complex.
  • Job Impact: While AI streamlines processes, concerns about job displacement in certain roles (e.g., pattern makers, retail assistants) are valid. The focus is shifting towards AI augmenting human creativity and creating new roles that require AI proficiency.
  • Environmental Footprint of AI: Training large AI models is energy-intensive. AI fashion brands must consider the energy consumption of their AI infrastructure to ensure it aligns with overall sustainability goals.

Despite these challenges, the trajectory for AI fashion brands in 2025 and beyond is one of relentless innovation. We can expect increasingly sophisticated virtual try-ons, hyper-customized on-demand manufacturing, and a deeper integration of AI across every touchpoint of the consumer journey. The future of fashion is undeniably intelligent, personalized, and, with responsible implementation, more sustainable. 

FAQs

Q1: What is an AI fashion brand?
An AI fashion brand utilizes artificial intelligence technologies to enhance various aspects of its operations, including design, production, inventory management, and customer experience.

Q2: How does AI personalize the shopping experience?
AI analyzes customer data, such as browsing history and purchase behavior, to recommend products tailored to individual preferences, improving customer satisfaction.

Q3: Are AI fashion brands sustainable?
Many AI fashion brands use AI to optimize inventory and reduce waste, contributing to more sustainable practices within the industry.

Q4: How is AI used in fashion design?
AI assists in fashion design by analyzing trends, consumer sentiment, and historical data to predict upcoming styles, enabling designers to create collections that resonate with consumers.

Q5: What role does Glance AI play in fashion?
Glance AI collaborates with fashion brands to enhance customer engagement by delivering personalized experiences directly to users' devices, aligning with individual preferences and shopping behaviors.


 

  


 

Glance

Ian Anderson is VP of AI at Glance, leading innovation in Gen AI, computer vision, and NLP. He holds a PhD in Mobile Computing and formerly led the Data Science team at InMobi’s Unified Marketing Cloud.

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