Reengineering Retail With AI

Implementing AI for Retail Experiences

Step into a modern clothing store and it might look like retail as usual. But if Alan Boehme, former CTO of H&M, had his way, it would feel more like entering a connected platform, where garments communicate, mirrors respond, and the line between online and offline disappears. At H&M, Boehme led technology innovation at scale, using artificial intelligence to create immersive in-store experiences, optimize sustainability, and democratize global experimentation.

“The way we have to look at innovation is that it comes from anywhere and everywhere in a corporation and around the world,” Boehme said. “It’s not bound by any geography anymore.” That mindset helped H&M blur the line between fashion, data, and artificial intelligence, especially when it came to transforming physical stores into intelligent retail environments.

A Live Data Layer for Inventory

Traditional retail inventory systems operate on batch cycles and approximations. H&M wanted something radically different: a real-time data layer that reflects exactly what’s on the floor, in the fitting room, or at the checkout counter.

“There’s a lot of RFID data locked in tags on garments,” Boehme explained. “We decided to lift the data out of our core warehousing systems, and we created a data layer in the store that now mimics what’s in the warehouse.”

The system uses 5G readers embedded in store ceilings and RFID panels in walls to track item-level movement with remarkable precision. “We can get 99% accuracy of everything that’s in the store at the same time,” Boehme said. That accuracy isn’t just for inventory, but foundational to a larger AI strategy.

“By lifting the data out and making it available using artificial intelligence and machine learning,” he continued, “it becomes more predictive.”

Smart Mirrors, Predictive Experiences

One of the most transformative applications of that predictive data is smart fitting room spaces that respond in real time to the shopper’s intent.

“When you pick a garment up and walk around the store, we know which are going into the fitting rooms and which ones are being left behind. Which ones are being tried on which ones are being returned to the rack,” Boehme described.

That interaction history could fuel recommendations through smart mirrors that not only recognize garments but can suggest complementary items, size adjustments, or even handle checkout. It changes the way retail companies can personalize the experience in-store.

The mirror becomes a real-time interface between the customer, product data, and AI algorithms, designed to enhance relevance. This isn't just digital convenience; it's a reframing of the store as a responsive, learning environment.

For Boehme, the fusion of AI and RFID was never just about tagging, but building a retail operating system that adapts. The store effectively becomes its own smart ecosystem, with inventory, consumer behavior, and purchasing data all flowing together. This opens up new levels of operational visibility, but also customer insight.

AI and the Circular Economy

Beyond customer experience, Boehme also viewed AI as a tool for solving one of fashion’s most urgent challenges: sustainability. H&M co-developed a system that reimagines textile reuse at the point of sale.

“We have a machine we helped co‑create which can take old clothing and actually consume it,” Boehme said. “It extracts the fibers and can create a new sweater for you very quickly.” This isn’t theoretical. Boehme described it as a real, operational innovation.

By integrating computer vision, machine learning, and material science, H&M’s AI-enabled recycling machine identifies fabric types, deconstructs old garments, and creates new ones on the spot. It’s a closed-loop system with dramatic implications for reducing fashion waste.

Redefining the Retail Role of AI

In every case, it was the convergence of AI with infrastructure, like RFID, 5G, and material sensing, that created business value. AI doesn’t work without data, and the data doesn’t work unless it’s in the right place, at the right time.

This meant rethinking how data flowed through the enterprise. It’s not about building another data warehouse, but rather about building a live data layer that supports real-time decisions. With that foundation, AI becomes a layer of intelligence and a framework for reshaping how stores behave, how products are designed, and how sustainability is measured.

Lessons Learned

Alan Boehme’s work at H&M illustrates a future where physical retail is anything but static. With AI acting as the connective tissue, every garment, room, and transaction becomes part of a larger feedback system.

From recognizing what’s tried on to forecasting what can be recycled, these systems automate and adapt. It’s about creating environments that understand what’s happening and respond in ways that are helpful, personal, and responsible.

The result isn’t just a smarter store. It’s a smarter industry that reuses more, personalizes better, and learns from every interaction.