For years, the potential disruption artificial intelligence poses to the global fashion industry has been reduced to a rather narrow question: how impressive can an AI-generated fashion image look?
Today, that question is not only too narrow, but falls short of the impact the new technology could have on an industry valued at $2.5 trillion and projected to grow to $3.326 trillion by 2031.
As someone who teaches fashion designers how to use AI for fashion visualisation, I have seen first-hand how quickly designers can move from an idea to a sophisticated visual concept. AI can generate a runway, a campaign, a model or an entire collection in seconds.
But fashion is not simply an image. A garment has to respond to a body, a fabric, construction methods, production realities, a customer and a market.
Looking at the Guess advertisement featuring AI-generated models that appeared in the August 2025 print edition of Vogue, I see more than the debate, which appeared to focus mainly on AI replacing models. I see an underlying issue of authenticity and creative labour.
When you look at the AI-generated model and her dress, a retro Mediterranean glamour reworked through contemporary, body-conscious resort wear, it is obvious that the question is no longer whether AI can generate fashion imagery. It clearly can.
The more difficult question is: what happens when almost anyone can generate an image that looks like a fashion design?
The gap between generating fashion and designing fashion
As a fashion designer with more than 10 years of industry experience and a fashion AI educator, I have seen an important misunderstanding emerge around generative AI.
Someone can prompt an image generator and receive a convincing gown within seconds. But producing an image of a garment is not the same as designing a garment that can be developed, fitted and produced.
An AI-generated image may show a dramatic sleeve without explaining how it attaches. It may create a silhouette that ignores fabric behaviour, body movement or pattern geometry. It can produce visually convincing details that become difficult or impossible to reproduce physically.
Recent research supports this distinction. A 2026 review of 57 peer-reviewed studies on generative AI in clothing design found that research is concentrated heavily on ideation and visual rendering, while pattern-making and structural design receive much less attention.
In other words, AI is increasingly good at showing what a garment could look like. This is one of the distinctions I emphasise when teaching fashion designers about AI. Visualisation is valuable, but it is not the same as solving all the problems involved in making a garment.
A trained fashion designer can look at an AI-generated design and ask questions the image itself cannot answer: Can this be patterned? What happens when the fabric moves? Where is the seam? How is the garment supported? Can it be graded across sizes? What will it cost to produce?
Those are not simply aesthetic questions. They are fashion-design questions.
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What happens when everyone can generate a ‘design’?
At the surface, just like with other areas where AI is being used, from software engineering, where vibe coding is becoming widespread, it appears that the barrier to producing a fashion image has fallen dramatically.
A person who has never studied fashion can now generate hundreds of visually appealing designs, experiment with fabrics and styling, select the most commercially attractive concepts and send them to a manufacturer.
Despite this reality, which is currently reshaping our industry, I believe that the barrier to producing a functioning fashion business has not disappeared.
Since a generated image does not automatically provide knowledge of pattern drafting, fit, textile behaviour, sampling, quality control, production costing or customer needs, fashion creatives are still required to understand these fundamental basics.
I envisage that the future of fashion in the era of AI will depend on the separation of the different stages through which a piece of fashion is brought to life.
Fashion designers or illustrators could decide to focus on creating the clothing concept, sketching it and choosing details such as silhouette, fabric, colours and construction. Using AI to aid their work, they could then give the design to a tailor, dressmaker or garment maker to produce.
Think of it as an architect who draws a building and then hands the master plan to a civil engineer who builds it. If the architectural design is flawed, the civil engineer would not be able to implement the plan properly. If they were forced to do so, there could be structural problems in the future that could result in the building collapsing.
Perhaps the time has come for fashion businesses to separate the various creative processes that lead to the making of a piece of fashion.
One person may generate the concept, another may develop the pattern, another may manufacture it and another may market it.
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The originality problem
If, as I have argued earlier, AI could usher in a true separation of roles in the creative fashion sector, the other issue that I believe deserves more attention is originality.
Fashion has always been built on references, archives, cultural influences and reinterpretation. Generative AI intensifies questions about where inspiration ends and imitation begins.
The issue becomes particularly sensitive when AI systems are trained on enormous quantities of existing creative work and then generate outputs that may resemble existing aesthetics.
Copyright law is still developing around these questions. The US Copyright Office has said that AI-assisted works can receive copyright protection where sufficient human creativity determines the expressive elements, while merely providing prompts does not, by itself, establish human authorship of the resulting material under its analysis.
However, when it comes to African fashion and the need to preserve the continent’s authenticity, a lot is at stake.
To begin with, it is estimated that the training data of major LLMs is 45 percent English-language content, while all African languages combined represent roughly 0.17 percent of the training dataset.
The implication of this is that Africa is already disadvantaged when it comes to how its culture, history and fashion are represented by these AI models.
Amid the shortage of reliable African-focused datasets, the issue of data privacy also rears its head.
How are African fashion creatives compensated for the use of their work in the training of LLMs? What happens if I take a photograph of my fashion design and upload it to the internet, and Google, OpenAI, Meta or Anthropic use it to train their models? How is my creativity compensated?
When fashion designers in other parts of the world can use AI and mass-produce implementable African designs, the future of the continent’s fashion industry, which is estimated to be worth about $31 billion and support 1.5 million jobs, hangs in the balance.
This is why it was heartwarming that in August 2025, Nigerian designer Ifeanyi Nwune of I.N Official collaborated with Meta on an AI-imagined collection presented at Africa Fashion Week London. Meta said its tools were used across colour and fabric selection, storytelling and visualisation, including generating ideas that combined African and Japanese design references.
The opportunity, therefore, is not just to use AI, but to carefully integrate African fashion creatives into the training of LLMs and ensure the recognition and, where appropriate, compensation of their creativity.
I believe that it is time for African fashion creatives to rethink their entire approach to the use of AI. Like many other sectors, the new technology will no doubt disrupt the fashion industry.
Ensuring that the mass production of fashion images without an understanding of the underlying principles that make up fashion does not replace the expertise of trained creatives, while carefully separating creative roles across the value chain and addressing questions of copyright and compensation, is crucial to capturing the full value of the rapidly booming African fashion industry.
Contributor’s Note: Victoria Jokotagba is a fashion designer, Fashion AI educator and Creative Director at Victoria Fashionpreneur and Concept Atelier Studio.
