Generative artificial intelligence has been pitched as the dawn of a more streamlined, cost and labor-efficient, and data-driven future for fashion. Through algorithms that use data and machine learning to create content, proponents say it has the potential to reinvent everything from design and forecasting to supply chain management and imagery, allowing for large-scale digitization of systems that have previously been scattered and incoherent.
Yet, more than a year after generative models first captured public attention, even the most advanced ones still fabricate facts, make basic math errors, and produce imagery with physical or historical inaccuracies. The reality is that while AI in fashion has potential, its adoption has been far from seamless.
The Hype vs. Reality
In 2023, analysts predicted that generative AI could boost the global fashion industry’s profits by up to $275 billion in three to five years, and billions in investment continue to flow into startups developing AI-powered tools. However, despite this enthusiasm, swift adoption remains uncertain. Between September 2023 and February 2024, businesses have not experienced the rapid AI-driven transformation that some anticipated.
Take Madeline, an AI shopping assistant launched by Kering. Promoted as the end of endless scrolling, it was designed to help consumers find luxury items effortlessly. Instead, its responses proved limited, robotic, and uninspiring. It failed to understand contextual needs, often suggesting products that were poor fits for occasions. Today, a notice on KNXT, the e-commerce site where Madeline was introduced, simply states that the project is “under maintenance” with no reopening date.
Levi’s also attempted to integrate AI in a bold way, using AI-generated models to enhance diversity in e-commerce visuals. The reaction? A wave of criticism. Instead of solving diversity issues, the initiative was seen as a way to bypass hiring real models from underrepresented backgrounds. The company has since abandoned its AI-generated model program, acknowledging that technology cannot replace the necessary structural efforts for true inclusivity.
The Hype Cycle: Where Does Fashion AI Stand?
New technologies often follow a well-documented pattern—the hype cycle. At first, excitement builds as early successes gain attention. Expectations skyrocket. But when projects like Madeline and Levi’s AI models fail to deliver, disillusionment sets in. This doesn’t mean AI in fashion is doomed. It simply means that the industry is moving past inflated expectations and into a more realistic phase of understanding what AI can and cannot do.
Tech watchdog Molly White put it bluntly: AI today is often “useful in the same way that it might occasionally be useful to delegate some tasks to an inexperienced and sometimes sloppy intern.” The problem isn’t just AI’s imperfections—it’s that businesses rushed into it expecting a revolution, when what’s needed is strategic and measured integration.
Where AI Works: Practical Applications
While some generative AI experiments have fallen flat, other applications are proving more promising. AI is not a replacement for human creativity—it’s a tool to enhance and accelerate processes. Here’s where AI is making an impact:
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Design Acceleration: AI-powered tools help designers create mood boards, predict trends, and experiment with variations faster than ever before.
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Marketing & Content Creation: AI-generated visuals, product descriptions, and campaign assets are streamlining workflows for fashion houses.
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Hyper-Personalization: Retailers are leveraging AI to analyze consumer behavior and refine recommendations, delivering more tailored shopping experiences.
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Digital Try-ons & Styling Assistants: Virtual fitting rooms and AI stylists help customers visualize outfits before making a purchase, improving engagement and reducing returns.
The Future of AI in Fashion: Evolution, Not Revolution
So, will generative AI take over the fashion industry? Likely not. But will it become an indispensable tool for brands looking to innovate? Absolutely.
The key is strategic adoption. AI in fashion doesn’t need to be revolutionary to be valuable. The challenge for forward-thinking brands like Zalmira isn’t just adopting AI but using it intelligently—in ways that enhance craftsmanship, creativity, and brand storytelling rather than dilute them.
AI is moving past the hype and into practical application. It’s not a magic solution, but it does offer tools that will refine, accelerate, and evolve fashion processes. Used wisely, AI can amplify creativity, support human ingenuity, and drive efficiency without replacing the essence of fashion itself.
The future of fashion is still human—but it’s one that will likely be shaped, in part, by AI.
