NRF has always been a reliable barometer for where retail is heading. This year, however, something felt distinctly different, explains Alexandra Considine Tong, Chief Product Officer, Retail Insight.

NRF is one of the few moments in the year when the industry collectively pressure-tests its assumptions. This time, the tone of those conversations had shifted.

Retailers were no longer debating what AI might make possible at some point in the future. Instead, discussions were anchored in practical questions about measurable value, speed to deployment and operational impact. The emphasis was firmly on proof: can it work in my stores, with my teams, at scale?


AI remained front and centre, but the sentiment around it has matured and the industry is moving beyond experimentation. Retailers are moving decisively from pilots to roll-outs and into a phase where operational impact matters far more than novelty.

From AI hype to everyday decision-making

What became clear throughout NRF is that retailers are increasingly seeking technology that can be fully embedded within their business.

AI is only valuable when it integrates with the rest of your technology landscape and when it influences the decisions people make every day.

To really move the dial, AI must be usable, explicable, and embedded in how store teams, supply chain leaders, and category managers actually operate. It is not enough to surface interesting patterns or correlations; the real test is whether those insights translate into confident action.

This is a healthy evolution away from AI for AI’s sake. Retailers are managing sustained margin pressure and heightened complexity, and in that environment, tools that create additional cognitive load or introduce ambiguity simply will not survive. AI must reduce friction, not add to it. It must support judgement, not attempt to replace it.

The most compelling examples at NRF were those that translated fragmented data into clear operational direction. They recognised that value is created not at the point of insight generation, but at the point of execution.

The store has become the real battleground

A second, consistent theme at NRF was that AI strategies ultimately succeed or fail in the physical store.

Retailers are doubling down on frontline execution and using AI to gain real-time visibility into what is actually happening on shelves. Missed sales, waste and availability gaps are increasingly viewed not as forecasting failures, but as execution problems that occur after the forecast is made.

Industry research suggests that between 65% and 80% of retailers are still operating with inaccurate inventory data. When systems suggest stock is available but shelves tell a different story, the impact is felt immediately: frustrated shoppers, lost sales, avoidable waste and significant rework for colleagues.

Crucially, many of these issues are not forecasting failures. They are execution failures that occur after the forecast has been made. Stock exists somewhere in the building, but not in the right place, at the right time, or in a condition that allows it to be sold.

In this context, AI’s role is to provide accurate visibility and prioritisation. Store teams do not need additional and endlessly complex dashboards; they need clarity on where intervention will make the greatest commercial difference. Regional leaders need confidence that they are directing effort toward the right stores and the right categories.

With annual store and supply chain labour costs running into the billions, even a small percentage of rework caused by poor execution represents an enormous drain on margin. AI’s role here is not to add to the proliferation of data points we expect store colleagues to consume, but to provide accurate visibility and prioritisation. Even marginal improvements in execution compound rapidly: small percentages matter. Precision matters.

Store Execution underpins the future of retail media

Retail media was another area where the conversation has matured. Retail media networks continue to attract significant investment, but brands are increasingly demanding clearer measurement, attribution and return on investment.

What is becoming clear is that the physical store is no longer just a point of sale, it is a measurable media surface. However, retail media can only succeed if the fundamentals are right. Accurate availability, range compliance and on-shelf execution are foundational. If promoted products are not available, if ranges are inconsistently executed, or if replenishment is unreliable, it is not just a missed sale; it undermines trust with shoppers and brands alike.

As retail media matures, the need for a trusted, operational version of the truth in-store becomes even more critical. Execution is no longer a back-office concern; it is a commercial capability.

Customer experience still matters, and technology enables colleagues to serve

Despite the focus on efficiency and margin, customer experience remained a recurring theme in discussions with retailers and technology partners alike. Shoppers still expect a seamless, frustration-free experience, one where they can find what they want, when they want it.

Encouragingly, many of the most thoughtful conversations at NRF also centred on colleague experience. Those conversations focused on how technology can remove unnecessary tasks, reduce complexity and direct teams to where they can make the greatest impact. When AI can remove low-value tasks, reduce ambiguity and provide clear direction, it strengthens rather than diminishes human judgement, and it frees colleagues up to focus on what matters most: their customers.

Technology should enable better coaching, better prioritisation and better decision-making at every level of the organisation. It should create confidence, not dependency. The goal is not automation at all costs, but a more human-centred retail experience, for both shoppers and store colleagues.

Proof, pace and outcomes now define success

Underlying all of these themes is a more disciplined investment climate. Large, multi-year transformation programmes that defer value are being scrutinised more closely. Retailers are favouring solutions that can demonstrate impact quickly and embed into daily operations without excessive disruption.

Retailers are also demonstrating a greater willingness to test, learn, and refine quickly. Rather than committing to large-scale programs with deferred returns, many are prioritizing focused deployments that can prove value in specific use cases before scaling more broadly. This iterative approach allows organizations to build confidence in what works operationally, while moving away from the expectation that transformation must occur through a single, large rollout.

This shift towards outcome-led partnerships is constructive. It demands evidence, clarity and accountability from technology providers. It also aligns technology investment more directly with commercial performance.

Looking ahead

NRF 2026 did not signal a retreat from AI. Quite the opposite. It marked a clear transition point for the industry, from research to application, from experimentation to execution and from insight to measurable outcomes.

The opportunity ahead is not about chasing the next buzzword. It is about helping retailers solve real, commercial problems consistently and credibly, particularly at the store level. Execution, proof, and outcomes are now the standards by which technology and technology partners will be judged.

The competitive advantage now lies not in adopting AI broadly, but in deploying it where it tangibly improves execution. For many retailers, that means focusing on the store floor, where strategy becomes reality, and margins are ultimately won or lost.

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