How Retailers Are Winning Big With AI: 10 Real Use Cases Transforming 2025 Commerce

Retail is experiencing the biggest technology shift in decades. With margins under pressure, fierce digital competition, and continuously evolving customer expectations, retailers are turning to AI and machine learning to unlock new levels of profitability and personalisation. With massive volumes of customer, product, and behavioural data scattered across channels, most retailers struggle to extract insights fast enough to influence real-time decisions. That’s exactly where modern Retail AI Use Cases are making a transformational difference.

AI helps retailers convert unstructured data into next-best actions—from personalised product recommendations and dynamic pricing to autonomous stores and hyper-efficient supply chains. According to McKinsey, companies that scale AI in retail can improve operating margins by up to 60%. Leading brands across beauty, fashion, grocery, luxury, QSR, and e-commerce are already proving the impact.

Below are ten powerful examples of Retail AI in action, demonstrating how some of the world’s biggest brands are rewriting the rules of retail.

• Sephora’s Virtual Artist – Reinventing Beauty Discovery: Sephora transformed beauty shopping with an AI-powered virtual try-on experience. Using facial recognition and augmented reality, the app scans each customer’s skin tone and features to recommend precisely matched foundation shades and personalised looks—boosting confidence and conversion.
• Olay Skin Advisor – Hyper-Personalised Skincare: Olay’s AI-powered Skin Advisor analyses selfies to assess skin age, hydration levels, and areas of concern, then creates a customised skincare routine that drives higher product adoption and brand loyalty.
• IKEA’s AI Sentiment Survey – Designing With Customers: IKEA uses AI-driven surveys to understand how customers want future AI assistants to behave. Insights around tone, personality, and interaction style help IKEA co-create AI-powered home experiences aligned with customer expectations.
• Target × Pinterest Lens – Visual Search Meets Retail: Target integrated Pinterest’s Lens visual search technology, allowing customers to photograph products and instantly find similar items—reducing search friction and accelerating purchase decisions.
• Knorr’s Instagram AI – Turning Memories Into Meals: Knorr introduced an AI tool that analyses Instagram photos using visual recognition to recommend personalised meal ideas and recipes, boosting engagement and emotional connection with the brand.
• Wheelys Mobile Market – The Self-Driving Store: Wheelys designed an autonomous, AI-powered mobile supermarket that travels to high-demand locations and returns to warehouses for restocking—showcasing the future of autonomous retail.
• Walmart’s AI-Powered Supply Chain & Last-Mile Delivery: Walmart leverages AI for demand forecasting, robotic picking, automated replenishment, and intelligent delivery routing—solving complex operational and last-mile challenges at enterprise scale.
• eBay ShopBot – Your Personal Shopping Assistant: eBay’s AI chatbot helps customers find the best deals across millions of products by learning preferences and remembering past searches, reducing decision fatigue and improving the shopping experience.
• Amazon’s AI Fashion Engine – Designing What Customers Want Next: Amazon uses machine learning to analyse global fashion trends and customer behaviour, predicting successful designs and even generating new styles to stay ahead in a fast-moving market.
• Alibaba’s FashionAI – The Smart Fitting Room Revolution: Alibaba’s FashionAI acts as a digital stylist in physical stores, recommending complementary items, sizes, and colours in real time to deliver a highly personalised in-store experience.

The Future of Retail Will Be Written by AI

From virtual try-ons and dynamic product recommendations to autonomous stores and predictive supply chains, AI is reshaping the retail value chain end-to-end. Global retail leaders are no longer asking “Should we adopt AI?”—they are asking “Where can AI create the next advantage?”

Retailers that embrace Retail AI Use Cases can accelerate profitability, reduce operational waste, and deliver hyper-personalised customer experiences that build long-term loyalty. As AI capabilities evolve—including generative AI, multimodal models, and edge-intelligent devices—AI-driven retail will become the industry norm.

Forward-looking retailers should begin building their AI foundation now through data readiness, AI maturity assessments, and targeted pilots. To explore how AI can unlock new revenue and customer growth opportunities, visit Inteliment’s solutions page or explore more insights on our blog.