8 ways AI will shape fashion commerce in 2025

1. Hyper-personalized marketing 

By analyzing customer data, AI can predict product preferences and deliver custom emails, ads, and content that resonate with each shopper. For example, you could build targeted email campaigns based on previous purchases or browsing behavior. This would allow you, for example, to show a select group of customers a new product as soon as it is released. Customers increasingly expect brands to understand and anticipate their preferences. By using AI to power hyper-personalized marketing campaigns, your brand has a huge opportunity to build a loyal following of brand champions. 

2. Turning inspiration into action with a visual search 

Fashion is a visually driven industry. That’s why AI-powered visual search tools are an increasingly influential way to let customers shop their way, using images rather than keywords. When a shopper uploads a photo of a look they love, visual search matches them with similar styles from a brand’s collection. This is not new technology. Brands like Forever 21 have leveraged visual search to boost product discoverability and capture purchase intent for years. However, as we move into 2025, the technology that supports visual search is improving rapidly. Not only is it easier for customers to find what they’re looking for, but visual search also taps brands into social media trends. 

3. Virtual shopping assistants for every shopper 

For many fashion e-commerce brands, recreating parts of the more personal touch of the in-store experience online is essential. AI-powered virtual assistants do that by offering styling advice and answering questions in real time. They can also make tailored product suggestions based on each shopper’s unique taste. For fashion brands, this is an excellent tool for grabbing and holding a website visitor’s attention and using it to drive conversions. Virtual assistants guide shoppers to products they’re likely to love, reducing the time to make decisions and boosting purchase rates. Furthermore, because the tech is relatively new, this level of personal attention makes your brand stand out in a crowded marketplace.

4. Personalize product recommendations 

With so many brands and products out there, customers increasingly rely on recommendations to help them make purchasing decisions. Getting product recommendations and bundles right is the holy grail for fashion brands that want to tap into the full potential of personalization and maximize the customer lifetime value of their shoppers. By analyzing browsing history, previous buyer behavior, and emerging trends, AI solutions can suggest items tailored to each shopper’s unique style. Leading brands like Amazon and ASOS have seen AI-driven recommendations significantly boost revenue by showcasing items that customers are more likely to buy. Accurate recommendations lead to bigger baskets and increased order value, making them an essential tool in any e-commerce strategy. 

5. Virtual try-on for better buying decisions

One of the most significant pain points when buying clothes and accessories online is the inability to try before you buy. This results in many returns as people buy the product to see whether it fits. With product returns an increasingly costly issue for apparel brands, AI is tasked with helping avoid this pain point. Indeed, augmented reality (AR) virtual try-ons, powered by AI, allow customers to see how clothing, shoes, or accessories will look on them. It is the next step for brands to bring online shopping closer to immersive in-store browsing. For fashion businesses, this is likely to have a direct impact on return rates, customer satisfaction, and, ultimately, brand loyalty. 

6. Chatbots for seamless 24/7 support 

We’ve all likely had some interactions with chatbots already – and maybe even been frustrated at their rigid adherence to the script. But those days are over, thanks to AI. Unlike basic bots that can’t deviate from pre-set answers, chatbot solutions in 2025 learn from each customer interaction, creating responses that feel more human and empathetic. This means fewer lost sales and happier customers. These bots handle routine queries, reducing operational costs while ensuring customers have a seamless experience – day or night. Similarly to shopping assistants, they can even advise shoppers on what sizes and cuts might work for them. 

7. Intelligent forecasting for smarter inventory management 

Inventory management is a constant balancing act in fashion. Fashion brands need to respond to ever-changing trends, but stockouts and warehouses filled with unsold products present a serious risk to profitability. AI can analyze historical sales, seasonal patterns, and trends to predict demand more accurately. By aligning inventory with demand, fashion brands reduce excess stock and improve sustainability – a key priority for today’s consumers. AI-driven forecasting helps brands minimize waste and streamline supply chains, keeping the right products available at the right time. For brands, this means a lower risk of markdowns, more efficient operations, and higher margins. 

8. Supporting sustainability with data 

Sustainability is increasingly front-of-mind for many fashion consumers. Luckily, AI is helping brands make environmentally conscious decisions. By analyzing data on sourcing, production, and distribution, AI identifies opportunities to reduce waste and minimize environmental impact. Many brands use AI insights to optimize material use and create transparent supply chains. For e-commerce fashion brands, sustainability is a powerful differentiator that builds customer loyalty and strengthens brand reputation in an eco-conscious market. 

inriver: The PIM built with AI

Outlined here is just the beginning. Over the coming years, AI is set to become even more integral to fashion e-commerce. Future advancements remain uncertain due to the rapid speed of innovation. Still, they could include virtual stores in the metaverse, where customers shop and try on outfits with digital avatars or even custom-made fashion pieces designed based on individual style data. 

However, successful AI adoption requires a complete and accurate foundation of data. Without getting the data foundation right first, any investment in AI and automation could result in a system that doesn’t work as well as it should. The good news is that if you have a PIM solution, you are already well on your way. By centralizing your data and making it consistent, you can be sure the data that AI uses is always up-to-date and compliant. 

The inriver platform offers the most flexible PIM software on the market. Built on the foundation of a fully adaptable data model, the inriver PIM solution is the perfect engine for any omnichannel strategy. Alongside the single source of truth for market-ready product information, the inriver PIM has API-based syndication and digital shelf analytics technology built in, giving you all the tools you need to succeed in today’s omnichannel world from a single, intuitive platform.

For more insight, watch Carhartt’s Director of Global Digital Operations, Anna Cole, in conversation with inriver experts here to discover how the global workwear giant uses data to drive revenue, reduce returns, and create seamless customer journeys.