NRF 2026: What Retailers Were Really Focused On

NRF 2026 made one thing clear: most retailers are no longer chasing flashy concepts. They’re trying to solve a set of stubborn, very practical problems:

• Seeing what’s actually on the shelf
• Reducing fresh food waste
• Making in-store fulfillment sustainable
• Helping frontline teams succeed

Here’s a concise recap of the main themes and some concrete approaches that came up in conversations at the show.

Inventory blindness: Seeing the real shelf, not just the system

Many retailers reported the same issue: systems show stock, but shoppers still find empty shelves.

Common pain points:

• Manual, sporadic cycle counts.
• Receiving errors that propagate through replenishment and e‑commerce.
• Limited trust in on-shelf availability data.

Practical approaches discussed:

• Moving from occasional counts to more frequent, lighter-touch checks using mobile devices.
• Capturing multiple barcodes in one view so teams can scan full bays, top stock, or back-of-house areas quickly.
• Turning shelf observations into ranked tasks (e.g. highest-impact gaps first) rather than static reports.

The underlying idea: make it easy for store teams to surface and fix issues as part of their normal routines, instead of treating accuracy as a separate project.

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Fresh food waste: Treating expiry dates as data, not a chore

Fresh and grocery retailers pointed to expiry as a major driver of waste:

• Date checks vary by person, time and store.
• Products close to expiry are hard to spot at scale.
• Markdown timing is often based on habit rather than insight.

Practical approaches discussed:

• Capturing both barcodes and printed expiry dates automatically, so checks can cover more items in less time.
• Aggregating expiry data to see patterns, for example, which SKUs or stores consistently drive higher waste.
• Triggering markdowns or removals from actual expiry data, rather than rough rules of thumb.

The shift is from “walk the aisle and eyeball dates” to “capture expiry once, then use it for both daily decisions and longer-term planning.”

In-store fulfillment: Making picking repeatable and scalable

As more orders are fulfilled from stores, retailers are re-evaluating how picking is done.

Key concerns:

• Time lost walking inefficient routes.
• Dependence on a small group of experienced pickers.
• Picking errors and mis-sorted items in totes.

Practical approaches discussed:

• Guiding pickers visually along an optimized route, rather than leaving path decisions entirely to individuals.
• Using the device camera to confirm the correct item on the shelf, especially where the packaging is similar.
• Showing on-screen which tote or compartment each item should go into to reduce sorting errors.

The aim is to make performance less dependent on “knowing the store by heart” and more on clear, simple guidance that anyone can follow.

Luxury & specialty: Keeping the conversation on the floor

Luxury and specialty retailers talked about a familiar tension: high expectations for service vs. the practical need to check stock and product details.

Typical challenges:

• Associates frequently leaving the customer to go to the back room.
• Fragmented access to product and inventory information.
• Clienteling tools that feel disconnected from the live interaction.

Practical approaches discussed:

• Giving associates a single, discreet device for both product information and stock checks.
• Ensuring that basic questions (sizes, variants, availability in nearby stores) can be answered without leaving the customer.
• Automating back-of-house tasks like inventory counting, product locating, and order assembly, so more time can be spent with customers.

The goal isn’t new technology for its own sake, but removing the small frictions that interrupt a high-touch interaction.

Three big questions retailers were asking themselves

Across different segments, three broader questions kept surfacing:

How do we reduce inventory blindness without overburdening stores?

Ideas included lighter, more frequent counts, better receiving support, and using shelf intelligence systems to cover more shelf in less time.

How far are our real shelves from our planograms?

Retailers are increasingly interested in “realograms”: a view of what the shelf actually looks like, captured regularly enough to spot gaps and non-compliance.

How does all of this connect to our wider ecosystem?

Many teams are thinking about how shelf and product data can feed analytics, AI initiatives and even retail media planning, ideally using the devices and cameras already in place.

Broader NRF themes: AI, media, and “quiet tech”

The show’s larger narratives aligned with these operational concerns.

Agentic AI

“Agentic AI” – systems that take actions, not just answer questions – was a major theme.

For stores, that raises a simple prerequisite: any agent making replenishment, pricing, or routing decisions needs accurate, timely information about what’s actually in front of customers.

That’s where consistent capture of item-level data (from shelves, stockrooms, and labels) becomes a critical input, not just a nice operational extra.

The store as a media asset

Retail Media Networks are moving into the aisle via digital screens, smart shelves, and app-guided journeys.

One implication: store execution (availability and pricing) and media performance are now tightly linked. If the promoted product isn’t available or correctly priced on the shelf, media results and shopper trust suffer.

That’s another reason accurate, near-real-time shelf data is becoming more important: it underpins both operations and media credibility.

“Quiet tech” and frontline work

Several speakers talked about “quiet tech”: solutions that:

• Improve inventory accuracy and shrinkage.
• Fit into existing workflows and hardware.
• Require minimal behavioral change for staff.

Alongside this, there was a clear focus on frontline experience in a tight labor market:

• Making complex tasks more guided and visual.
• Reducing training time for new staff.
• Designing tools that feel closer to consumer apps than traditional enterprise systems.

Computer vision and mobile workflows were often positioned as ways to incrementally improve the workday. Less hunting, fewer repeated scans, clearer next steps, rather than as dramatic, one-off transformations.

Key questions retailers should be asking post-NRF

Whether or not you attended NRF, the discussions suggest a few useful prompts for internal conversations:

• How confident are we in our on-shelf availability numbers, store by store?
• Where are expiry dates and other key attributes still being handled manually?
• How big is the gap between planograms and what customers actually see?
• How easy is it for a new associate to pick accurately, count stock, and verify prices?
• Are our AI, analytics and retail media efforts grounded in reliable, real-world store data?

Answering these doesn’t require starting from scratch, but it often does mean looking at how existing devices, cameras, and workflows could be used differently.