NRF 2026: What To Expect at Retail’s Big Show Next Year

Unified Commerce and Spatial Computing

Last year, unified commerce drew considerable interest, particularly from brands struggling to modernize their digital storefronts and unify online and in-store experiences. That continues to be a priority, Szanger says, and retailers can expect demos tied to major commerce platforms including Adobe, Salesforce and Shopify.

Unified commerce has become a critical priority for retailers because it ties together every shopper touchpoint — online storefronts, mobile apps, point-of-sale (POS) systems, loyalty programs and fulfillment operations — into a single, coherent platform. When these systems operate in silos, retailers struggle with inconsistent inventory visibility, uneven customer experiences and manual workarounds that drain resources. A unified approach enables real-time data sharing across channels, which in turn supports faster transactions, more accurate personalization, and smoother transitions between digital and physical shopping journeys. As the industry faces rising expectations around convenience and consistency, unified commerce isn’t just a technical upgrade; it’s table stakes for competing in a modern retail environment, in part because it sets the stage for AI projects that have meaningful impact on sales.

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Spatial computing, meanwhile, is an emerging category that blends virtual and augmented reality (AR) experiences using VR headsets such as the Apple Vision Pro. Retailers are recognizing that such technology can help them more effectively design stores and create immersive training experiences for new employees.

CDW, for example, is developing a training application for restaurant workers, Szanger said. The demo places a user inside a virtual kitchen and guides them through a hands-on task — for example, assembling a burger — with real-time scoring and gamified efficiency prompts. “There’s a lot of food waste associated with in-kitchen training, and it slows operations down,” Szanger says. “This lets employees practice, improve and stay out of the way before they ever touch real ingredients.”

The underlying development capability can be customized for use across restaurants, retail, manufacturing, healthcare or any environment where consistent, repeatable training is critical. It also reflects a growing trend at NRF: interest in practical, business-aligned AR/VR deployments rather than speculative demonstrations.

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AI Takes Center Stage With Real Operational Use Cases

AI has been an NRF talking point for years, but this year the discussion shifts from abstract potential to real operational impacts. Szanger says retailers are trying to understand where AI pays off first and how fast they can move from concept to customer-facing value. “The companies that are getting hands-on with AI now are already separating themselves from those waiting to see how things play out,” he notes.

One major theme that retailers will likely discuss at the show is AI-driven customer interaction. Brands are looking beyond chatbots on websites and toward more sophisticated, multimodal interfaces that can handle natural language, offer personalized recommendations and reduce friction during peak-volume moments. Szanger points to fast-evolving “virtual human” technologies — lifelike digital hosts that can check in guests, manage queues, answer product questions or assist with “buy online, pick up in-store” workflows. These systems are becoming increasingly realistic, multilingual and adaptive. The value proposition is clear: shorter waits, fewer bottlenecks and more consistent service, even when stores are understaffed.

Retailers are also exploring how these tools can operate deep inside the shopping experience rather than being confined to the front counter. A virtual assistant positioned in a high-question aisle — power tools, paint, home electronics — could help shoppers find the right replacement part or accessory without relying on the availability of a roaming associate. As labor challenges persist, Szanger expects strong interest in how AI can extend service coverage without compromising quality.

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Another major thread he sees gaining traction is AI-supported store operations, particularly around inventory accuracy and replenishment. Out-of-stocks remain one of retail’s most expensive — and most solvable — problems. Szanger highlights growing interest in systems that combine POS data, environmental factors such as local weather patterns and store-defined thresholds to automatically flag when shelves need to be restocked. “Retailers lose sales every day not because they’re truly out of an item but because the product is sitting in the back room,” he says. AI-based triggers give managers real-time visibility into those gaps and help associates respond before the customer encounters an empty shelf.

The same principle applies to emerging tools that help frontline workers become more effective, especially when dealing with massive assortments. Szanger points to voice-enabled assistants that let employees query product information instantly — for example, asking for the replacement battery for a specific power tool without leaving the shopper’s side. “It keeps the associate with the customer, speeds up service and builds confidence on both sides,” he explains. Paired with image-recognition tools that can identify a part from a photo and surface compatible alternatives, the technology promises to shrink training time and boost first-contact resolution.

If there’s a throughline to all of these conversations, it’s that retailers want AI that solves today’s problems, not hypothetical ones. They’re looking for tools that reduce wait times, eliminate manual work, improve workforce productivity and make stores feel more responsive. As Szanger puts it, “The shift this year is toward AI that can be implemented, integrated and scaled, not just piloted.”

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