The Future of Fashion and Productive Artificial Intelligence

We examined the role of productive artificial intelligence (AI) in the fashion industry, which has the potential to make companies more productive, enter the market faster, and provide better service to their customers.

You've probably heard of ChatGPT, the AI chatbot from OpenAI that created a sensation overnight and initiated a digital race to create and launch competitors. ChatGPT is just one consumer-friendly example of generative AI, a technology that includes algorithms used to generate new content, including sound, code, images, text, simulations, and videos. Generative AI, which utilizes deep learning models capable of simultaneously performing multiple complex tasks rather than just identifying and classifying information, is behind innovations such as GPT-3.5 and DALL-E.

While the fashion industry has experimented with fundamental AI and other cutting-edge technologies like the metaverse, NFTs (non-fungible tokens), digital identities, and augmented or virtual reality, it has had little experience with generative AI until recently. This emerging technology has only recently become widely available and is still fraught with concerning complexities and errors, yet all indications suggest that it could rapidly evolve and potentially change the rules of the game in many areas of the business world.

According to McKinsey analysis, within the next three to five years, productive AI could contribute up to $275 billion or, conservatively, $150 billion to the operating profits of the apparel, fashion, and luxury sectors.

From accelerating design to content development processes, productive AI is creating a new frontier for creativity. It can handle all sorts of "unstructured" data, such as raw text, images, and videos, and generate new media formats ranging from fully written scripts to 3D designs and realistic virtual models for video campaigns.

The Future of Fashion and Productive AI

While it may be a bit early to discuss these, some clear use cases for productive AI in fashion are already emerging. Particularly in areas such as product innovation, marketing, sales, and customer experience, this technology could yield significant results, and its implementation in the short term may be more feasible compared to other areas of the fashion value chain.

On the other hand, productive AI is not just about automation but also about augmentation and acceleration. This means providing technological tools to fashion professionals and creatives to perform certain tasks significantly faster and freeing them up to dedicate more time to tasks only humans can do. Establishing systems to better serve customers could also fall into this category. So, where do you start?

Productive AI has the potential to impact the entire fashion ecosystem. Companies in the fashion sector can use this technology to create better designs, reduce marketing costs, hyper-personalize customer communication, and streamline processes. Additionally, they can reshape supply chains and logistics, store operations, and organizational support functions.

Would you like to take a closer look at AI? We're listing the areas of application and applications that shape the future.

Product Development and Innovation

Both mass-market fashion retailers and luxury brands' creative directors can use productive AI to analyze various unstructured data types in real-time rather than relying solely on trend reports and market analysis to determine the designs for the next season's collections. For example, productive AI can quickly analyze emotions from videos on social media or model trends from multiple consumer data sources.

Creative directors and teams can transfer sketches and desired details such as fabrics, color palettes, and patterns to a platform supported by productive AI, which automatically generates a range of designs, allowing designers to play with a wide variety of styles and looks. A team can then design new products based on these outputs, each bearing the signature of a fashion house. This opens the door to the creation of innovative, limited-edition products that could be collaborations between two brands. Products like glasses can be designed for individuals using productive AI-supported face recognition technology to scan facial topography and adjust based on the customer's body and style preferences.