Puma Unveils AI-Designed Sneaker, Sparking Debate on Creativity

Artificial intelligence (AI) is rapidly reshaping how major fashion brands conceive and design products, highlighted by Puma’s release of a new AI-developed sneaker this month.

The growing adoption of AI tools in fashion houses’ design studios signals a fundamental change in an industry long defined by human sketches and handmade prototypes. Questions about creativity and craftsmanship arise as more brands experiment with computer-generated designs to stay competitive in a fast-moving market.

“AI is shaking up the everyday notion of how fashion designers craft their designs,” Fameez Haroon, co-founder at fashion company OTAA, told PYMNTS. “In the past, creating an entire fashion collection could take an unreasonable amount of time, from simple hand sketching to assembling fabrics and fittings, and so on. AI tools like algorithms and generative design platforms offer new perspectives.”

Puma’s AI Shoe

Puma’s Inverse shoe exemplifies the integration of AI into design, combining archival inspiration with modern technology. The shoe features a red mesh upper, midsole cage, and ProFoam cushioning. 

Lead Product Line Manager Scottie Gurwitz noted in a news release, “AI doesn’t abide by the same rules as human designers, helping us see things in new ways.” Global VP of Creative Direction Heiko Desens added, “The precision of AI is a new tool to level up our design.” 

Over the past year, AI’s influence has grown more visible, with high-profile collaborations and innovative uses changing how collections come to life.

Take the recent partnership between Chinese artist Lulu Li and luxury brand Moncler. Using AI platforms like Runway and Midjourney, Li designed a line of down jackets and vests that debuted at Moncler’s “City of Genius” event in Shanghai. The results showcased AI’s ability to assist designers in creating complex, visually stunning garments.

AI is enhancing creativity and sharpening fashion’s ability to predict trends. Companies like Heuritech are harnessing AI to scan thousands of social media posts daily, offering real-time insights into consumer preferences. Brands use this data to stay ahead of the curve, ensuring their collections align with rapidly shifting tastes.

The rise of digital fashion has also been fueled by AI. Platforms such as DRESSX are creating virtual clothing, enabling users to “wear” digital outfits in photos and videos. DRESSX launched an augmented reality app that lets shoppers try on digital pieces from brands like Balenciaga and Bershka, blending innovation with sustainability.

AI is even modeling the clothes. Retailer Mango faced backlash this year for using AI-generated models in its advertising, raising concerns about authenticity and the impact on jobs in the modeling industry.

Meanwhile, generative AI tools are democratizing design. Platforms like Off/Script let users input written prompts to create their own clothing designs, empowering consumers to take part in fashion’s creative process.

Creative AI?

The use of AI in fashion design has raised questions about originality and intellectual property. AI often creates by analyzing large datasets of existing designs, sometimes leading to works that resemble existing creations. For example, Shein has faced lawsuits alleging its AI tools reproduced patterns similar to independent artists’ designs. Similarly, debates arose when AI-generated patterns were used in collaborations like Collina Strada’s Baggu project, sparking concerns about the ethical boundaries of using AI in creative industries.

According to Haroon, AI can generate numerous design variations from a single idea, reducing the need for extensive human input. “This allows designers to think outside the box,” Haroon explained. Tasks that might traditionally take an entire day can now be completed in a few hours, freeing designers to focus on innovation. He pointed to AI’s integration into production processes, such as fabric selection and pattern design, which empowers designers to adapt to evolving fashion trends more efficiently.

“Even though AI is trained on ‘past data’ — the information it has been introduced to before — you can toggle certain parameters to introduce entropy or the randomness in the output,” Jenny Wang, founder of the personal style companion Alta, told PYMNTS.

“This can result in more interesting variations and creative ideas that can form the basis for new trends. At Alta, our data also shows us how varied and creative every shopper’s style is from the next person. We maintain personalized AI experiences for each consumer that reflects their own unique style and point of view.”