Transformative Power of AI in Fashion

With its rapid development, artificial intelligence (AI) has the potential to become one of the most revolutionary technologies the fashion industry has seen in decades.

In this extensive overview, we examine how generative AI (GenAI) is quickly changing fashion - once a slow-moving industry - into a data-driven, highly creative, and individualized environment. (Spoiler: you will still need a mirror to check if a garment fits you).

How AI technologies revolutionize fashion

Fashion brands are testing the waters with technologies that can forecast fashion trends from social media patterns, automate some manufacturing processes, and produce realistic garment imagery from text prompts.

The Business of Fashion (BoF) and McKinsey’s "State of Fashion 2025" report presents AI, especially GenAI, as an influential force in the fashion industry in the face of changing consumer habits and economic uncertainties.

Many facets of the textile business are being revolutionized by the introduction of AI technology, with the latter being used in textile manufacturing and development, design, quality control, supply chain management, and improving customer experience.

Current AI applications in fashion

More than 85% of executives believe that AI will be a major factor in company strategy, making it an essential component for innovation.

However, they highlight the importance of value-focused uses, which means using AI to bring genuine benefits, such as:

• Improving products and customer experiences.

• Assisting employees in improving their effectiveness.

• Making better business decisions, and more.

Although many projects involving AI are still in the early stages of testing, those brands that will be able to integrate the technology successfully could gain a competitive edge in sustainability, customization, and curation.

Area	Top AI Use Case	Expected Impact	Example Brands/Platforms
Product Discovery	Generative AI for search/curation	Higher engagement, reduced research time	Zalando, TikTok Shop, Pinterest
Inventory	Demand forecasting	20% accuracy improvement, less waste	Kering
Sales	Training tools	15-20% higher order value	Reiss
Operations	Marketing & cost reduction	Efficiency in descriptions, logistics	Frasers Group

Now let’s examine these in more detail:

1. Product discovery

Fifty percent of fashion executives believe that GenAI could be extremely helpful for consumers when they search for a product.

AI-driven technologies are changing the way consumers find and engage with items, and in e-commerce, this is seen to be one of the keys to increasing client happiness and subsequently conversion rates.

• Multi-modal AI (processing text, images, audio) will redefine how consumers find products.

• Open-source models from Google (Gemini) and Meta (Llama) are accelerating innovation, helping smaller players compete.

• Multi-brand retailers will invest in AI-driven personalized search.

Case studies:

1. Zalando is investing in AI assistants to improve output accuracy through user feedback. Its generative AI tools use user data to curate content in real time.

2. With 60% of consumers finding new businesses through focused searches, TikTok GenAI tools speed up the creation of content for brands.

3. Pinterest's AI Collage tool increases engagement for posts that include shoppable products by making the site more shoppable.

2. AI in inventory management and forecasting

AI can be extremely important when it comes to improving demand prediction and cutting waste to address excess inventory - a billion-dollar problem in the fashion industry.

Advanced analytics may help brands align with consumer needs, reducing shortages and overstocking.

Case study:

Luce, Kering's clientele software, gives retail employees customized product suggestions and customer-specific promotions. During the app’s early deployment period in 2018-2019, the average order value increased by 15-20%.

3. AI in sales and customer experience

AI enhances human factors in retail by empowering employees and customizing interactions, particularly when in-store buying is on the rise.

Experts believe that AI can help transform the role of store staff in fashion retail:

• Companies should train and equip employees with tools that use data to better understand customers and products.

• It’s important to reward staff not just for in-store sales but for building long-term customer relationships across online and offline channels.

• Fashion brands should aim to use AI to automate routine tasks.

Case study:

Fashion retailer Reiss has teamed up with Thrive Learning's AI-powered platform to improve employee skill development for 1,300 staff members across the United Kingdom, Europe, and the United States.

4. AI in operations

AI is highly regarded for essential tasks like logistics planning and product descriptions.

Marketplaces can (and should) use AI for both frontend (tailored content) and backend (optimized traffic), which could be beneficial during share price declines (with an emphasis on ethics to minimize risks).

Case study:

Various marketplaces use AI to cut expenses. For instance, in online shopping, they use AI-powered size recommendations to assist clients in selecting the appropriate size, thus minimizing product returns.

The intersection of AI and consumer behavior

AI is making the fashion consumer's journey much more individualized. Nowadays, as firms use algorithms that learn from browsing history and social media data, online buyers receive carefully selected product recommendations based on their preferences.

On the other hand, customers are also having a direct impact on fashion by creating content (writing online reviews, posting outfits, etc.), which feeds the AI's data for identifying emerging trends.

AI-driven design innovations

Fashion design is experiencing a creative explosion thanks to generative AI technologies, but AI's effects extend beyond sketches and designs; it is also changing the materials and fabrics we wear.

AI enhances fashion design creativity

With the help of AI image generators and assistants, designers can rapidly come up with creative new outfits by entering ideas or sketches and allowing the algorithm to make creative adjustments.

Here’s one example:

AI can examine enormous collections of fashion photos to recommend new patterns or color schemes, providing designers with a wealth of inspiring ideas.

The impact of AI on materials and textile development

Previously, to come up with a special fabric, one had to carry out time-consuming trials in labs, but today, machine learning models are far quicker than humans at predicting material qualities and suggesting new fiber or treatment combinations.

AI vision systems in manufacturing are also helpful in textile quality control, identifying subtle defects or color irregularities, guaranteeing that the materials used to make our clothing are of the highest caliber.

In the video below, Professor Aron Walsh of Imperial College London describes how AI could improve the discovery of materials by assisting researchers in predicting novel materials with certain features:

Sustainability and AI: The greener side of fashion

In the fashion business, sustainability is a major concern, and artificial intelligence is becoming an important tool in the effort to make the sector greener.

Utilizing AI for waste reduction and resource optimization

Overproduction has been one of the main issues facing fashion retail; when brands misread trends, they wind up with mountains of unsold inventory.

AI systems assist brands in forecasting which styles will likely sell better and in what quantities. This is because these systems can analyze:

• Historical sales.

• Real-time shopping behavior.

• Social media buzz, and more.

It's a win-win situation: companies save both time and money, while fashion's environmental imprint lessens.

Apart from production, AI also optimizes the use of resources across the supply chain via:

• Routing shipments with higher efficiency (saving fuel).

• Managing power usage in plants.

• Automating processes to cut on water usage.

Brands such as Heliot Emil, Zara, and H&M are already using AI to control supply chains, which they say promotes sustainability by reducing overstock and waste.

Trend prediction AI: Fostering responsible consumption

Today, to predict which designs are becoming more popular, companies use AI-driven analysis to sort through a vast amount of data, including street style photographs, Instagram posts, runway photos, and Google searches.

It’s possible that soon we might witness AI trend alerts that not only inform you about what’s in at the moment, but also identify lasting designs or upcycled fashion trends.

Consumer experience revolutionized by AI

AI is revolutionizing online clothes purchasing by providing intelligent assistance and personalization. The tech can act as your stylist, while virtual shopping assistants can make your shopping experience more comfortable.

Personalization in fashion shopping: AI-powered recommendations

These days, recommendation algorithms customize suggestions for items based on the preferences of each user, displaying bohemian gowns to one and minimalist streetwear to another.

Companies like Stitch Fix use AI “personal stylists” to create entire ensembles based on past purchases and quiz results.

Customers may preview how clothing will appear on their avatars or selfies with virtual try-on tools driven by AI and augmented reality (AR).

Here’s an example of Google's "Try On":

Chatbots and AI assistance: Enhancing customer support

If you open an online fashion store nowadays, there’s a good chance a chat window pops up offering help.

AI chatbots have turned into the new digital shopping helpers, already used by companies like ASOS and H&M, where they assist customers with checkout, provide sizing guidance, answer questions, and recommend products in real time.

More advanced "virtual stylist" bots even suggest entire ensembles for important events or assist customers in updating their wardrobes.

Future outlook: AI’s trajectory in fashion

Given the breakneck pace of innovation, the next few years promise even more surprising AI advancements in fashion.

1. AI styling assistants

It's not difficult to imagine a future in which you point your phone at someone's gorgeous jacket on the street and an AI will direct you where to buy it (or a similar product).

2. Virtual try-on experiences

Better generative imagery and augmented reality could potentially allow you to view yourself in front of a mirror while dressed entirely in digital clothing that moves and drapes like the real thing.

3. AI may play a bigger part in the production process automation

AI advances could eventually convert a digital design straight into machine instructions for sewing and cutting.

4. Behavioral shifts

• Customers are also creators, curating and producing material that encourages interaction, according to research from Wear It AI with 20,000-plus users.

• New indicators like try-on frequency, peer influence, and content-led transactions better capture the impact of AI, while traditional metrics, including likes or impressions, overlook important information.

5. Designing and prototyping

AI is already helping creators and small businesses to directly capitalize on their ideas by reducing entry barriers for development, manufacturing, and marketing using technologies that automate tasks and deliver data-driven insights. This includes:

• Using GenAI for design ideation and pattern creation.

• Coming up with AI-powered marketing campaigns.

• Using AI-driven platforms for customization, virtual try-ons, and direct-to-consumer sales.

The financial benefits of adopting these technologies

Experts forecast that by 2034, the global AI in luxury brands market size will be valued at US$5.6 billion (from US$1.2 billion in 2024), registering a CAGR of 16.2% during the forecast period.

It’s worth noting that in 2024, North America held a strong market position with over 33.4% share and a US$400 million revenue, according to market.us.

Final word: Embracing the AI fashion revolution

AI is changing the way trends are anticipated, items are designed and manufactured, and people discover and enjoy style.

Furthermore, AI has led to increased customization while also driving the business to be more sustainable and responsive.

Rather than destroying creativity or originality, AI applications in fashion enhance both, providing designers with powerful tools and consumers with more voice and choice.