NRF Europe 2026 recap – Part 1 of 2
The Next Now: How AI Is Rewiring Retail
Part 1 of our two-part recap of NRF Europe 2026. Part 2, on AI Assistants and the practical steps retailers can take towards autonomous reatil, is coming soon.
“The Next Now” was the theme of NRF Europe 2026, held in Paris from September 15–17. The message was clear: the future of retail is no longer something to prepare for – it is something retailers need to act on now.
But what does this mean in practice? Exploring and experimenting with AI is no longer enough. To truly move ahead, retailers need to move beyond individual use cases and build the capabilities, data, technology, and operating models required to scale AI across the business.
Opportunities and obstacles
According to the McKinsey & Company and EuroCommerce study “Rewiring retail in Europe: The AI imperative”, AI is already reshaping the European retail value chain, with a €240 billion to €320 billion opportunity at stake. The greatest opportunity lies in the Commercial-Merchandising domain, with an overall EBITDA improvement of 2–4%, followed by Marketing (1–3%), and Commercial-Buying, Omnichannel Operations, and Supply Chain & Logistics (1–2% each). The study suggests that retailers should anticipate total technology investment of around 1.5–5% of revenue, depending on company size and maturity, with the AI-led portion increasing.
Unfortunately, most retailers are not prepared to grab this opportunity. Nearly nine in ten companies report adopting AI, yet just as many report no meaningful impact on the bottom line – a disconnect that many executives describe as the “AI paradox”. Over 80% of retailers remain at an emerging state of AI literacy and adoption. The main reasons they cannot scale AI towards ROI are organizational rather than technical. The biggest constraints preventing scale are:
From technology adoption to business transformation
These results show that technology and culture change must go hand in hand.
“Ultimately, winning with AI is above all a question of culture, teams, and ways of working.”
Christoph Eltze, Chief Digital & Technology Officer, Rewe
Żabka proved this with its transformation from Polish corner stores into a popular high-street convenience chain, with over 13,000 stores in Poland and over 200 in Romania. Żabka is currently the biggest pizza retailer in Poland, with more than 4 million transactions per day.
Alongside investing in technology, assortment and offer optimization, customer engagement, and omnichannel capabilities, Żabka has prioritized a change of culture inside the organization. Not only did it restructure the company to attract young talent, it also involved the team as part of the evolution. Empowered by data and embedded AI, franchisees and employees can run daily operations more efficiently – for example, through an application franchisees use to manage inventory and store planograms. This changed the mindset: technology is there for people, not to replace them. The result is a team that shares the company’s vision and pushes together towards a common goal.
With AI, up to 75% of roles will change, so a fundamental rewiring of the entire enterprise is required. High-performing retailers have adapted their organizations across six core capabilities: strategy, data, technology, talent, workflow, and governance.
Case in point: Debenhams
The British heritage brand Debenhams shows how far this rewiring can go. Economic difficulties forced it to close its physical stores, so it redesigned the company completely as an online marketplace. Debenhams now leverages AI strategically for merchandising and customer engagement, and has brought in brands it does not produce itself to give customers more choice and increase the likelihood of a sale. It has since become a destination of choice for fashion, home and beauty – and has no plans to return to the high street.
AI in action
Today, retailers are primarily using AI for two purposes: improving operational efficiency and enhancing customer engagement. This aligns with another keyword of NRF Europe: Connected. Next-generation retail is about using AI to connect transactions, inventory and operational systems, stores, and customers – enabling retailers to turn connected data into better strategic and operational decisions, and to respond with greater speed and agility.
Operational efficiency
Across retail, AI is moving beyond experimentation and individual use cases to address concrete business challenges and deliver measurable improvements. The most effective applications are not necessarily the most complex; they are often those that connect technology with existing processes to make operations faster, more agile, and more responsive to customers. Examples from retailers across Europe show how AI and intelligent technologies are being embedded into everyday operations:
Electronic shelf labels allow faster price updates in response to competitors – and have increased in-store picking efficiency by more than 10%. With “Pick by Light”, each picker is assigned a dedicated color and picks the products whose shelf label lights up in that color.
Combines Python code with large language models (LLMs) to improve the quality and speed of translations.
Redesigned internal processes originally built around human intervention to better leverage AI, addressing data fragmentation and inefficiencies across its logistics operations.
Intelligent order management enables delivery within one hour. Store employees handle the picking while an aggregation tool consolidates orders from multiple platforms; once a store reaches a defined order threshold, further orders are automatically routed to other stores.
The opportunity is not simply to adopt more technology, but to use it to simplify complexity, connect the business, and empower people. By applying AI to the operational challenges that consume time and resources, retailers can free their teams to focus on what matters most: building stronger connections with customers and delivering better experiences.
Customer engagement
In our 2020 article “Enabling an Emotional Connection with Your Customers”, we explored how growing social isolation is increasing consumers’ desire for emotional connection through retail. Customers want to feel recognized, understood, and part of a community, rather than being treated as just another transaction. That has not changed. If anything, younger generations increasingly expect to be not only emotionally engaged, but physically and sensorially involved in the experiences brands create.
One common application, highlighted by Mango and MediaMarkt at NRF, is using AI to provide inspiration, personalization, and conversational support through chatbots. But while online interaction keeps growing in importance, physical stores remain critical to building relationships. They offer human connection, sensory experiences, and the immediate gratification of discovering and buying products – things online retail cannot fully replicate. Galeries Lafayette illustrates the link between channels: 40% of its web customers also purchase in store, and despite strong e-commerce growth, store visits have not declined.
French natural cosmetics retailer Aroma Zone is another example of connecting online and offline. It began as an online retailer with a rich knowledge base that helped customers learn about essential oils and natural cosmetics. When it expanded into physical stores, it turned them into immersive learning environments where customers can touch and smell products, get advice from staff, and join workshops. The journey begins online, where customers explore and learn, and continues in store, where they experience the products and deepen their relationship with the brand.
Retailers are also experimenting with new ways to anticipate customer needs and remove friction from the shopping journey:
Immersive rooms let customers visualize furniture in their own surroundings, projected onto the walls.
Known for its “naked” packaging, Lush has explored virtual reality as a way to tell the stories behind its products.
Its innovation lab is experimenting with digital twins of stores and augmented-reality overlays that could help customers navigate stores more easily and personalize product experiences.
With Shop-to-Light, the app directs customers to the right aisle; when they arrive, the matching electronic shelf label flashes so they can find the product quickly.
Ultimately, technology should make the customer experience more seamless, relevant, and effortless – not more complicated. By reducing friction and offering relevant information, inspiration, and support, it helps customers make better decisions and feel more confident in their choices. That is how retailers move beyond optimizing individual transactions to building lasting relationships: when customers feel understood, supported, and connected to a brand, they have more reason to return, engage, and spend time with it.
Coming soon: Part 2
This was part 1 of our NRF Europe 2026 recap. In part 2, we will explore the next wave of AI-driven retail trends and outline practical actions retailers can take to turn these emerging opportunities into tangible business value.