Generative AI for Fashion and Retail: Applications, Benefits, and Challenges

We have an innate capacity for creativity that enables us to generate, transform, and communicate information in novel and meaningful ways. The fashion and retail industry is no stranger to innovation, but the rise of Artificial Intelligence is transforming the way designers and entrepreneurs approach their craft. With the power to create, innovate, and personalize products like never before, generative AI is opening up a world of possibilities. Data shows that in 2018, the global AI in the fashion market generated a staggering $270 million, and experts predict that this figure will skyrocket in the coming years. With a projected CAGR of 36.9% from 2019 to 2027, the market is expected to reach an astonishing $4.4 billion by 2027.  This surge in growth is a clear indication of the increasing adoption of AI technology in the fashion industry, and the enormous potential it holds for revolutionizing the way we approach design, manufacturing, and retail. From intelligent trend forecasting to personalized fashion recommendations, generative AI is already reshaping the industry, and the possibilities are endless. In this article, we delve into the specific ways in which generative AI is revolutionalizing the fashion industry and the challenges and opportunities it presents to designers, enterprises, and consumers.

Applications

The world of fashion has always been a hotbed of innovation and creativity, where designers constantly push the boundaries and explore new frontiers in their designs. As reported in the LFW briefing by Glossy, for their latest runway show, Shanghai-based brand KWK by Kay Kwok collaborated with a sound artist who used ChatGPT to generate lyrics that played out alongside an accompanying violin. While some may dismiss AI as a marketing ploy, designers are increasingly using generative AI to inform marketing music, seasonal designs, and even supply chain traceability. And, as the use of AI in fashion evolves, we can anticipate even more exciting developments that will forever change the way we think about fashion. Here are some of the most notable applications of generative AI in fashion and retail:

1. In establishing your own brand

In the fiercely competitive fashion industry, it's crucial to establish a unique brand identity that sets you apart from the crowd. And that's where generative AI comes in - it can help you create fresh, eye-catching designs that capture the attention of your target audience and establish your place in the industry. Despite being a complex and daunting process,  with the assistance of AI, the process of creating a brand from scratch can be streamlined and made more efficient. The initial step in establishing a brand is to create a design brief, which involves determining the brand's target audience, values, mission, and tone of voice. Language models like ChatGPT can prove to be a useful tool, providing a valuable resource for developing a comprehensive design brief. Once the design brief is in place, the next step is to establish the brand's visual identity. This entails selecting color palettes, typography combinations, and other visual elements that reflect the brand's image. The AI can provide numerous options from which to choose, enabling the creator to select those that best align with their vision for the brand. There are numerous AI tools available that can help expedite the logo design process like Midjourney, Dall-E 2, and Stable Diffusion. Additionally, AI can be used to generate product photography for the brand. One of the most compelling benefits of using AI to establish a brand is the swiftness with which it can be accomplished. By employing these generative tools, the entire branding process can be completed in just a couple of days, which is significantly less time than it would take to do so manually.

2. Product development

With its ability to generate new images and content, AI can help fashion designers create entirely new designs or refine existing ones using the latest trends and consumer preferences. Generative AI enables your designers to input their desired parameters and constraints into the algorithm, such as the desired aesthetic, materials, and target market. From there, the AI algorithm works its magic and creates entirely new fashion designs based on these parameters, opening up endless creative possibilities for designers. Another exciting feature of generative AI is style transfer, where designers can apply the style of one design to another, creating variations on existing designs or combining elements from different sources. This allows designers to experiment with different styles and create unique pieces that stand out in the crowded fashion landscape. Generative AI also has the power to help retailers and manufacturers optimize their product development process by predicting demand and identifying the most popular designs and trends. By analyzing data on consumer preferences, AI algorithms can provide you with insights that help your business make informed decisions about product development, pricing, and marketing strategies.

3. Trend forecasting

The fashion industry is facing significant challenges in trend forecasting due to the rapid turnover of styles and the increasing influence of social media on consumer behavior. With the emergence of new products, styles, and trends every week on social media, your brand must anticipate time-to-market speed to remain competitive. However, manual or digital observation and data collection from fashion designers and influencers have traditionally been labor-intensive and time-consuming. By analyzing large volumes of social media data, generative AI can identify emerging trends and predict consumer preferences that may not be apparent to human analysts. Generative AI can also help your brand generate new design ideas by combining elements of existing designs and identifying new design possibilities which can give your brand a competitive edge by providing you with a unique and fresh perspective on design. Generative AI can also optimize the production processes of fashion brands by predicting demand for specific products and identifying the most efficient production methods. This can help reduce waste and improve supply chain efficiency, leading to cost savings and increased profitability.

4. Product description generation

In December 2022, Hong Kong-based fashion designers from the Laboratory for Artificial Intelligence in Design (AiDLab) wowed audiences with their revolutionary fashion show that showcased generative AI-supported designs. Thanks to cutting-edge tools provided by tech giants like Cala, Designovel, and Fashable, these designers were able to leverage the power of generative AI to unleash their creativity and experiment with countless design variations without the need for costly prototypes. This results in a streamlined design process that has the potential to transform the fashion industry as we know it. With generative AI, you can analyze large volumes of data on fashion styles, trends, and product features to create descriptions that are tailored to your specific audience and product. This means that you can highlight the unique selling points of each dress, such as its style, fit, and comfort, in a way that resonates with your target customers. Using generative AI to create product descriptions can free up your time and energy, allowing you to focus on other aspects of your business. Instead of spending hours agonizing over every word in your product descriptions, you can let generative AI do the heavy lifting, while you focus on designing, marketing, and growing your business.

5. Sales, marketing, and consumer experience

The benefits of generative AI in fashion extend beyond just design. Retailers can implement this technology in their e-commerce and online marketing strategies to enhance the customer experience and ensure more sustainable production processes. Generative AI is revolutionizing the way fashion brands approach marketing by enabling them to personalize their offerings and optimize their engagement with customers. generative AI assists in designing captivating emails, website pages, captions, and ads that are customized to individual interests, thereby increasing the likelihood of customer engagement. Generative AI's ability to plot creative and authentic marketing and ad content that stands out in search results provides fashion brands with a competitive edge in today's crowded marketplace. By leveraging generative AI, fashion brands can optimize their marketing efforts to reach a broader audience and maximize their return on investment. With the ongoing evolution of e-commerce, generative AI is becoming increasingly popular among retailers as it allows for more accurate product recommendations and efficient search and discovery. This not only enhances the customer experience but also helps fashion brands establish a more significant online presence and drive sales. For instance, by using generative AI to develop unique designs and patterns, retailers can offer customers more personalized products that meet their specific tastes and preferences. This can increase customer satisfaction and loyalty, leading to higher sales and revenue. Moreover, generative AI can help retailers make their production processes more sustainable by reducing waste and optimizing resources. This can reduce the environmental impact of production processes and contribute to a more sustainable fashion industry.

6. Your very own fashion brand consultant

With AI algorithms that analyze data from social media and fashion blogs, fashion businesses can identify emerging trends and create designs that resonate with their target audience. Companies can optimize their pricing strategies by analyzing customer behavior and demand patterns, allowing them to set prices that maximize profits while keeping customers satisfied. Beyond pricing, generative AI also provides valuable insights into the preferences and behaviors of target customers, enabling businesses to create effective brand strategies. This includes identifying the most effective marketing channels and messaging for different customer segments. Imagine a cosmetics brand using generative AI to create targeted ads for customers who are interested in natural and organic products. By understanding customer preferences, businesses can craft messages that resonate with their audience, increasing brand loyalty and sales. Businesses can optimize inventory management by predicting demand and identifying the optimal quantity of products to produce. With AI, a shoe company can produce the right amount of a new style based on customer demand data, reducing excess inventory and improving profitability. This reduces waste and minimizes costs while ensuring that products are available when customers want to buy them. 

7. Supply chain optimization

One way that generative AI can be used in optimizing the supply chain is by forecasting demand. AI algorithms can analyze historical and synthetic data to predict future demand with greater accuracy. This helps businesses to manage their inventory levels more efficiently, reduce waste, and ensure they always have the right amount of stock. By leveraging AI, Farfetch enables its 1,500 boutique partners and 200+ brands to seamlessly connect their online inventory with their physical stores, facilitating services such as click-and-collect and in-store returns. It can also optimize production processes by analyzing historical data and simulating different scenarios. The algorithms can identify the most efficient and cost-effective production processes, leading to reduced costs, improved quality, and faster production times. AI algorithms can identify the most efficient shipping routes and delivery schedules, reducing transportation costs and improving delivery times.

8. Fashion Education

In a bid to support and enhance the design processes of future designers, Microsoft has made significant investments in educating them on how to effectively use AI technology. This move is expected to enable future designers to harness the power of AI to bolster their design processes. In order for fashion brands to benefit from technologies like AI and ChatGPT, they need to have a good understanding of these technologies and use them at scale, emphasizes Aileen Carville, the founder of virtual asset management company Asset Haus. This means that fashion designers need to invest in educating their staff to help them become familiar with the technology and new digital workflows. From designers to marketers, sales associates, and customer service representatives, all members of the organization can benefit from incorporating generative AI tools into their workflows. Fortunately, some businesses have already recognized the importance of AI-focused training and have introduced programs to equip their employees with the necessary skills and knowledge.

The Benefits of Generative AI in Fashion and Retail

Generative AI is transforming the fashion retail industry in exciting and innovative ways. From efficiency to sustainability, virtual try-on technology to customized production, this technology is making waves and helping companies stay ahead of the game.

Efficiency

The fashion retail industry can greatly benefit from generative AI's efficiency by automating repetitive and time-consuming tasks. This technology can tag products, categorize images, and manage inventory, freeing up valuable employee time and resources to focus on higher-value tasks such as customer service and product development. Generative AI can also help retailers optimize the supply chain by predicting demand, ensuring a steady flow of inventory, and reducing the risk of overstocking or understocking products.

In addition to these benefits, generative AI can also automate the design process, significantly reducing time to market and design costs. By analyzing real-time data such as sales trends and stock levels, this technology can automatically replenish low-stock items or reduce the inventory of slow-moving items, improving searchability and enhancing the customer experience.

Sustainability

The fashion industry is notorious for being one of the most polluting industries in the world, with textile waste being a major contributor to the global waste problem. Generative AI can help combat this issue by providing insights into the most sustainable and eco-friendly materials, processes, and practices.

Through the analysis of large amounts of data, generative AI can identify and recommend sustainable materials and production methods that are better for the environment. This can include materials made from recycled or biodegradable materials, as well as more energy-efficient production processes that reduce waste and emissions. By adopting more sustainable practices, companies can not only reduce waste and emissions but also appeal to environmentally conscious consumers who are increasingly concerned about the environmental impact of their purchases.

Virtual try-on and Augmented reality

Luxury brand Cartier has introduced a hyper-realistic augmented reality (AR) technology that allows customers to try on its expensive rings without actually owning them. The technology was developed by the Cartier Retail Innovation Lab in Brooklyn using generative AI. To try on the rings, customers wear a simple marker ring with a raised dot, which is captured by a lamp equipped with cameras and sensors. The technology then superimposes the Cartier ring onto the customer's hand in real-time, creating a 4K resolution image that is virtually indistinguishable from reality. Cartier's AR try-on technology is a testament to how virtual try-on and augmented reality are closely related concepts in the fashion retail industry. 

Virtual try-on technology allows customers to virtually try on clothes and accessories without physically trying them on. By uploading a photo of themselves or using their device's camera, they can see how a product will look on them in real time. However, virtual try-on technology can still feel disconnected from the shopping experience, as customers are simply seeing themselves in the product, rather than interacting with it. This is where, by overlaying digital content in the real world, augmented reality can make it feel like the customer is actually interacting with the product. For example, a customer could use their smartphone camera to see how a pair of shoes will look on them and then virtually walk around in them, seeing how they would feel in real life.

By enabling customers to see how a product will look and feel on them before making a purchase, retailers can reduce the number of returns due to sizing and fit issues, which ultimately reduces waste and improves sustainability. Additionally, by creating a more immersive and interactive shopping experience, retailers can increase customer loyalty and drive sales.

Customization at scale

Generative AI can enable companies to produce customized products at scale, reducing waste and increasing efficiency. By using algorithms to generate designs and patterns that meet the unique requirements of individual customers, companies can manufacture products that are tailored to each customer's specific needs and preferences. In addition, generative AI can also be used to create personalized fashion recommendations based on a customer's individual style preferences, body type, and past purchase history. This can help retailers provide a more curated and personalized shopping experience for their customers, increasing customer loyalty and satisfaction.

Overall, the ability to create customized products at scale through the use of generative AI not only meets the growing demand for personalized products but also offers significant benefits in terms of efficiency and sustainability.

Being Aware of Risks and Challenges

“Digital artist Rutkowski's signature style has become one of the most widely used prompts in Stable Diffusion. However, his name has been used as a prompt around 93,000 times in just one month by open-source AI art generators raising concerns about ethics and copyright among artists, including Rutkowski and Karla Ortiz. Rutkowski fears that the flood of AI-generated art could eventually make it difficult for him to find his own work on the internet. Will AI-generated art threaten the livelihoods and rights of human artists?”

The fashion industry has long been known for its complex copyright environment, and the increasing use of AI is likely to agitate the situation even further, making it more vulnerable to copying and infringement. Companies will find it easier to create and produce knock-offs of popular designs as generative AI is quickly integrated into every segment of the fashion value chain, from product discovery to robotic manufacturing. The question of whether generative AI-generated material is copyright-protected remains a major concern, and the use of both human-authored and AI-generated material raises additional registration and copyright issues. This could lead to a significant loss of revenue for original designers and brands, who have invested a lot of time and resources in developing their unique creations. For instance, in the graphic novel "Zarya of the Dawn", which uses images generated by the AI service Midjourney combined with human-authored text, the Copyright Office determined that the work as a whole is copyrightable but the individual AI-generated images are not. This begs the need to determine whether works consisting of both human-authored and AI-generated material can be registered and what information should be provided to the office by applicants seeking to register them.

This has implications for the fashion industry, where the use of generative AI may result in designs and other creative works that blur the lines between human and machine authorship. As such, the industry will need to navigate the complex copyright environment and determine how to protect and monetize AI-generated works while ensuring that they do not infringe on the rights of human creators.  Moreover, employees who use generative AI may not be fully aware of its limitations and may overlook errors introduced by the technology. To minimize these risks, fashion executives should establish a process for addressing risk, ethics, and quality assurance, and provide employees with regular training to ensure they understand how to use the technology effectively. Despite these challenges, the potential applications of generative AI in the fashion and retail industry are vast, and we are only just beginning to scratch the surface of what this technology can do. 

Take the Right Approach

As machines become increasingly capable of producing original works of art and design, what does this mean for the role of human creativity in society? Will we come to value the unique perspective and insight that only humans can provide, or will the efficiency and precision of generative AI ultimately prove more valuable in the marketplace?

As we navigate this new era of technology, it will be important for leaders in the fashion and retail industry to consider the impact of generative AI not just on their bottom line, but on the larger societal implications of this technology. The global apparel market is projected to reach $2.25 trillion by 2025, making fashion one of the largest industries worldwide. While artificial intelligence may not be the first thing that one associates with fashion, industry insiders suggest that designers and brands who adopt the latest technology will have the upper hand in this rapidly evolving sector. Experts believe that companies that incorporate AI into their business models will be better equipped to keep pace with changing consumer preferences and demands. By taking a thoughtful and intentional approach to the integration of generative AI into your business, you can ensure that your company is harnessing the full potential of this technology while also upholding the values and principles that define our human experience. Ultimately, the impact of generative AI on the fashion and retail industry will depend on how we choose to use it.