London-based designer Kanyinsola Onalaja has revealed how artificial intelligence played a crucial role in salvaging her debut at London Fashion Week after a fire destroyed more than a decade of her work. With just three months to prepare, Onalaja turned to Adobe Firefly, a generative AI tool, to accelerate her design and sampling process while preserving her creative vision and the intricate craftsmanship her brand is known for.
According to reports from The Business of Fashion, Onalaja faced the daunting task of rebuilding her entire archive and collection in a fraction of the usual time. The fire, which wiped out years of hand-embellished womenswear rooted in Yoruba and Edo heritage, left the designer with limited resources and a tight deadline ahead of one of the fashion industry’s most significant events.
Onalaja explained that Adobe Firefly enabled her to rapidly generate design concepts and visualise samples, a process that would typically take months using traditional methods. The AI tool allowed her to experiment with patterns, colours, and embellishments, helping her to quickly iterate and refine ideas without sacrificing the brand’s signature attention to detail.
Founded in 2014, Onalaja is known for its maximalist approach and commitment to craftsmanship, offering inclusive sizing from XXS to 4XL. The brand’s reputation for scarcity—driven by the real constraints of artisanal production rather than manufactured hype—has resonated with consumers seeking authenticity in luxury fashion, according to The Business of Fashion.
Despite the rapid turnaround, Onalaja emphasised that generative AI was used to support, not replace, the handwork and artistry central to her designs. She maintained that every piece in the new collection underwent the same level of detailed craftsmanship as before, with AI serving as a tool to streamline the creative process rather than automate it.
The use of AI in fashion remains a contentious issue, with many designers and industry insiders debating its impact on creativity and authenticity. Onalaja’s experience highlights both the potential and the limitations of generative AI in high-end fashion, particularly when faced with unforeseen challenges such as the loss of an entire archive.
Industry observers note that brands are increasingly finding success with products that are scarce due to genuine constraints, such as the availability of materials and the time required for skilled craftsmanship. This trend stands in contrast to the engineered scarcity of limited-edition drops, which some consumers have grown weary of.
Onalaja’s swift recovery and successful presentation at London Fashion Week have drawn attention to the evolving relationship between technology and tradition in the fashion world. Her story underscores the resilience and adaptability required to navigate an industry where both innovation and heritage are highly valued.
Why it matters
Onalaja’s use of Adobe Firefly to rebuild her collection demonstrates how generative AI can serve as a lifeline for designers facing unexpected setbacks. By enabling rapid prototyping and visualisation, AI tools can help preserve creative intent and craftsmanship even under extreme pressure, as shown by Onalaja’s experience following the studio fire.
This case also illustrates a broader shift in the luxury fashion industry, where consumers are increasingly drawn to products with genuine scarcity and artisanal value. According to The Business of Fashion, brands like Onalaja that prioritise craftsmanship over manufactured hype are finding renewed relevance among discerning shoppers.
As the fashion industry continues to grapple with the integration of new technologies, Onalaja’s approach offers a model for balancing innovation with tradition. The story signals that, while AI can accelerate certain processes, the core values of creativity and craftsmanship remain central to the appeal of high-end fashion.
The image accompanying this article is an AI-generated illustrative depiction inspired by the actual scene of the event.































