5 Fashion Brands Already Using AI (and What We Can Learn From Them)

Levi’s – AI-Generated Models for Inclusive Product Photos

Levi’s made headlines by partnering with Lalaland.ai to create AI-generated fashion models for its e-commerce photography. Instead of relying only on one or two human models per product (the industry norm), Levi’s can now quickly generate diverse virtual models of different body types, ages, and skin tones to “expand the number of models per product” and let customers see clothing on people who look like them . The goal is a more personal and inclusive shopping experience without having to stage dozens of costly photoshoots.

This approach is also pragmatic. As Lalaland’s founder notes, shooting every outfit on 9 different human models isn’t feasible for most brands – “they’re not just hiring models, they’re hiring photographers, hair stylists and makeup artists” for each shoot . AI avatars cut those production costs and time. Levi’s is clear that AI models will supplement, not replace, real models , but they see big potential in using AI to scale up content. Lesson: Even an iconic denim brand finds value in AI to broaden representation and efficiency. We learn that AI can help scale personalization (more models, more inclusivity) in a cost-effective way – as long as you balance it with authentic human storytelling to keep it real.

Mango – AI-Generated Fashion Campaign Imagery

Spanish fashion retailer Mango became one of the first to launch an entire campaign created with generative AI. In mid-2024, for its teen line “Sunset Dream” collection, Mango’s design and photo teams collaborated with AI to produce photorealistic campaign images . They first took real studio photos of each garment, then trained a generative AI model to “position the real garments on a model” and generate on-brand visuals . The biggest challenge? Achieving the same editorial quality as a normal fashion shoot. Mango’s team ended up hand-retouching and fine-tuning the AI images to meet their standards – and the results were strikingly realistic (the AI-generated scenes looked like real photos shot at a Moroccan desert backdrop) .

Mango proudly calls this “the first fashion campaign generated entirely by AI” , but it’s not a gimmick – it fits into a larger strategy. The company has built 15+ machine-learning platforms since 2018, applying AI in pricing, personalization, design inspiration and more . For example, Mango uses generative AI to help designers brainstorm prints and even to visualize store window displays . Lesson: Mango’s experiment shows how AI can augment creative workflows. By treating AI as a “co-pilot to amplify our creativity” (in the words of their CTO) , the brand sped up content creation while maintaining quality. We learn that being an early adopter of AI in marketing can set you apart – but success comes from blending human creativity with AI efficiency, not replacing it.

Nike – AI-Powered Storytelling and Virtual Try-Ons

Global sportswear giant Nike proved that AI can elevate storytelling in marketing. To celebrate Nike’s 50th anniversary, they created an 8-minute ad called “Never Done Evolving” featuring a tennis match between two versions of Serena Williams – Serena in 1999 vs. Serena in 2017, digitally brought to life by AI .

Using machine learning on archival footage, Nike’s agency AKQA simulated 130,000 points of gameplay between the two Serenas to model their playing styles . The final video – essentially Serena vs. her younger self – was a hit. 1.7 million viewers watched the AI-match on YouTube, an 1082% increase in organic views compared to typical Nike content . It broke Nike’s records for engagement, showing how innovative content can captivate audiences.

But Nike isn’t just using AI for splashy ads. They’ve long invested in practical AI-driven tools to enhance customer experience. A great example is the Nike Fit app, which uses AI and AR to scan your feet via smartphone and recommend the perfect shoe size . This not only personalizes the shopping experience, it also led to fewer returns and higher customer satisfaction (better fit = happier customers) . Nike’s also leveraging AI in product design and athlete performance data .

Lesson: Nike shows that AI can be both flashy and functional. A bold AI-driven campaign can build brand buzz and emotional connection (people love a good story), while practical AI tools can solve customer pain points day-to-day. We learn to think creatively – how can AI help tell your brand’s story in a way that engages millions? – but also to use AI to improve the basics like helping each customer find their perfect fit.

Image: Nike’s “Never Done Evolving” campaign used AI to pit 1999 Serena Williams against her 2017 self in a virtual tennis match, attracting record engagement . It’s a prime example of AI-powered storytelling in sports marketing.

Shapermint – AI Streamlining Influencer Content Creation

Not only big brands are in the game. Shapermint, a DTC shapewear brand, built an AI tool in-house to supercharge its social media marketing. Their team developed an AI agent called “Altair” that generates scripts and storyboards for TikTok and Instagram influencer videos . Essentially, the AI analyzes what’s trending and crafts video briefs for creators, suggesting everything from story beats to caption ideas. The human influencers still film the content, but Altair handles the heavy lifting of ideation and planning.

The impact? Within 9 months of rolling it out, Shapermint’s CMO said Altair cut their influencer content production time by ~70% . A single marketer could strategize 4–6 videos per campaign per influencer much faster than before. This efficiency boost let Shapermint scale up – they expanded to new platforms (like YouTube Shorts and Pinterest) using the time saved and increased their influencer content budget by 20% to amplify reach .

The payoff has been tangible: the company expects a 35% jump in revenue (to $300M) year-over-year, which the CMO directly credits to the AI-assisted, high-volume creator strategy . Importantly, Shapermint was realistic about AI’s limits – the tool doesn’t auto-generate actual video footage (they found current AI video quality too low) , but it excels at the planning stage.

Lesson: A smaller brand can do more with less by using AI for content generation behind the scenes. Shapermint’s team freed up creative hours and doubled down on what worked. We learn that AI can automate tedious creative prep (like writing dozens of video scripts), enabling your team and partners to produce far more content without burning out – a critical advantage when marketing budgets are tight and “more with less” is the mantra.

Depop – AI-Generated Product Descriptions and UGC Support

Even resale and smaller e-commerce players are harnessing AI to remove friction. Depop, the popular fashion reselling app, introduced a generative AI listing tool in late 2024 that can write product descriptions from a single photo . For a busy seller, this is a game changer: just upload your item photo, and Depop’s AI will auto-suggest a title, category, color, and a fun description with relevant hashtags – all in the casual, quirky tone that Depop’s Gen-Z community likes. During beta tests, nearly 50% of sellers who had access used the AI description generator, indicating real appetite for this help . Depop’s goal is clear – if listing becomes easier and faster, users will list more items, sell more, and ultimately stay on the platform longer .

Depop isn’t alone here. Major marketplaces like eBay and Amazon have launched similar AI tools for sellers. In 2023, eBay rolled out a “Magical Listing” tool that generates descriptions based on photos (much like Depop’s) and an AI tool to automatically clean up or replace photo backgrounds for a professional look . Amazon integrated an AI to draft product bullet points and titles for its sellers .

Even Google jumped in with a Product Studio that can generate new product images or backgrounds on the fly . All these innovations point to a trend: AI is becoming the silent assistant for user-generated content in eCommerce. Lesson: Lowering the content creation barrier for your users or team can drive real results.

We learn that by embedding AI help into the selling or content process (whether for your internal team or your customers), you enable more output and a better experience. In Depop’s case, sellers save time and can list more items – which grows the whole marketplace. Consider where AI can similarly reduce friction in your business.

Image: Depop’s fashion resale app now uses generative AI to help sellers create listings. Sellers can upload a photo, and the app suggests a description, category, and hashtags in Depop’s signature style . By speeding up UGC creation, Depop hopes users can list more, sell more, and contribute to a “more circular fashion economy” .

Key Takeaways for Brands

AI in fashion isn’t sci-fi or a future gamble – it’s happening now, delivering practical wins for those who use it smartly. As a marketing lead who has worked with many brands on digital strategy, here’s what I take away from these examples:

• Start with a Real Problem: Each of these brands applied AI to a specific challenge – be it generating more diverse product photos (Levi’s), speeding up content production (Shapermint), or automating tedious listing tasks (Depop). The best AI projects have a clear purpose tied to ROI (e.g. reducing costs or boosting conversion)  .
  
  
• Human + AI = Better Together: A common theme is augmentation, not pure automation. Mango’s and Levi’s teams still did styling and retouching ; Shapermint’s creators still film videos; Nike’s campaign leaned on human creativity to frame the story. Successful brands use AI as a “co-pilot”  – accelerating creative and decision-making processes while preserving a human touch for quality and brand voice.
  
  
• Measure the Impact: These cases show notable results – from 15–20% boosts in conversion (AI recommendations) to 70% faster production cycles  to 10x engagement on campaigns . Track the metrics that matter for your use case (time saved, engagement gained, revenue lifted) and publicize those wins internally. It builds momentum and buy-in for further AI investment.
  
  
• Stay Authentic and Ethical: Audiences can be thrilled by AI creativity (Nike’s ad) but also wary of it. Transparency and brand integrity matter. Levi’s, for example, had to clarify that AI models won’t replace real diversity efforts  . If you venture into AI-generated influencers or images, be prepared to address the “is it real?” questions. Authenticity is still king – use AI to enhance it, not erode it.
  
  

Finally, as a marketer in 2025 I’ll say this: don’t be intimidated by AI, but do be intentional. The fashion brands winning right now are those experimenting and learning. You don’t need a tech giant’s budget – tools are more accessible than ever – but you do need a clear strategy and a creative mindset. Start small, learn from pioneers like the ones above, and keep your customer experience front and center. In an era where “over half of eCommerce businesses have adopted AI” , the risk isn’t adopting AI too early – it’s being left behind if you don’t.

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