Artificial intelligence is about to radically change the landscape of the fashion industry

Fashion is a dynamic sector. Most clothing brands earn at least two to four collections per year. When marketing current seasonal collections, brands plan the next ones at least a year in advance, identifying market trends and materials. The sales window is about three months and unsold inventory represents a financial loss.

Fast fashion companies are introducing new lines even more frequently, reducing the time it takes to design, produce and market new items.

Technology and fashion

The fashion industry has a history of pushing the boundaries of technology. Some of the most significant technological advances include laser cutting, computer-aided design, and more recently, the use of 3D printing in early 2010.

The fashion industry has been experimenting with Basic AI and other cutting-edge technologies. An example is the Gucci gardenthe labels' collaboration with virtual world platform Roblox in May 2021 to celebrate the brand's centenary.

Non-fungible tokens (NFTs) are another area of ​​innovation, as shown in the Dolce & Gabbana Genesis Collection in collaboration with UNXD, a luxury digital marketplace. This collection was sold for 6 million US dollars, set NFT sales record.

Fashion companies are also using blockchains for product authentication, traceability and digital identifiers, among others. those integrated by LVMH/Louis Vuittonauthentication and traceability of products.

Additionally, businesses have integrated augmented reality into their marketing and retail strategies to create immersive and interactive customer experiences.

Revolutionary technology

In 2021, fashion companies invested between 1.6 and 1.8 percent of their revenues in technologyBy 2030, this figure is expected to increase to between 3 and 3.5%.

Generative AI could be a game changer for the fashion industry, adding between $150 billion and $250 billion operating profits within three to five yearsAlthough the fashion industry is only just beginning to integrate AI, the opportunities and challenges it presents are evident across all business processes.

Generative AI could help fashion companies improve their processes, get products to market faster, sell more efficiently, and improve the customer experience. Generative AI could also support product development by analyzing large datasets from social media and runway shows to identify emerging fashion trends.

Este Lauder Companies and Microsoft have partnered to open a internal AI innovation lab to identify and respond to trends, inform product development and improve the customer experience.

Designers could use AI to visualize different materials and patterns based on consumers' past preferences. For example, Tommy Hilfiger is collaborating with IBM and the Fashion Institute of Technology in New York on the Reimagine Retail Projectwhich uses AI to analyze consumer data and design new fashion collections.

Designers can also convert sketches and mood boards into 3D designs and 3D print them to speed up prototyping. Iris van Herpen, a Dutch fashion designer, used AI to imagine and execute the visuals of its fall/winter 2023 collection.

AI and sustainability

AI is helping to create more sustainable fashion practices by optimizing resource use, recycling materials, and reducing waste through more precise manufacturing processes and efficient supply chain and inventory management. For example, H&M uses AI to improve recycling processessort and categorize clothes to recycle them and promote a circular fashion economy.

AI can improve supply chain operations and processes by optimizing inventory management, predicting sales based on historical data, and reducing overstocks and stockouts. Brands like Zara and H&M are already using AI to control supply chainspromoting sustainability by optimizing stock levels and reducing waste. Zara also introduces AI and robotics in their retail stores to speed up the pickup of online orders.

AI-powered virtual try-on solutions allow customers to see what clothes will look like without physically trying them on, improving the online shopping experience and reducing return rates. Virtual try-ons are already a reality in digital businesses, such as eyeglass retailer Warby Parker And Amazon.

Another example is Amendedacquired by French multinational personal care company LOral in 2018, which offers augmented reality-based virtual try-ons for makeup and fashion accessories.

An effective campaign

AI can also deliver personalized customer experiences. Some brands, like Reebok and Versaceinvite their customers to use AI tools to design products inspired by the look and feel of brands.

AI-powered tools can help marketing teams target and maximize the impact of their communications campaigns, potentially reducing marketing costs.

The fashion industry spans from small businesses to global chains, from haute couture to ready-to-wear, mass market and fast fashion. Every brand needs to understand where AI can drive value for their business without diluting their brand identity.

The biggest challenge, however, is to avoid homogenization. Generative AI should not replace human creativity, but create new spaces and processes.

Creativity and innovation remain the soul and heart of any fashion brand, and AI must be a tool to enhance and support them. As fashion designer Hussein Chalayan said, fashion will be renewed thanks to technology, new fibers, new ways of making clothes.

The Pitfalls of AI

Fashion companies must be prepared to manage the risks associated with new technologies, particularly with regard to intellectual property, creative rights and brand reputation. One of the main issues is the potential infringement of intellectual property related to training data.

GenAI models are trained on large design datasets, often containing copyrighted works. This can lead to legal disputes originality and appropriationA related risk is that of bias and fairness in generative AI systems, which can present reputational issues for brands that rely on this technology.

Another concern is the ambiguity surrounding creative rights in the age of AI. It’s difficult to determine who owns the creative rights to a design—whether it’s the designer who conceptualized the idea, the developer who created the AI, or the AI ​​itself. This ambiguity can dilute the authenticity of a brand’s creative expression, which can harm its reputation if consumers perceive the brand as less innovative or authentic.