Andrew Blackmore, Head of Data, Retail Media and Monetisation, VusionGroup UK & Ireland 

Technology has transformed the way we shop. From the emergence of e-commerce and online marketplaces to rapid home-delivery, technology has driven significant structural changes in the retail sector.  

But retail’s adoption of emerging technology is now lagging behind, especially on the shopfloor. Financial services, industrials and even defence have harnessed, at scale, data and AI for years. Meanwhile, too many retailers rely on fragmented data and analysis platforms, outdated systems and inconsistent execution. The result isn’t just lost revenue – for some retailers, this will become a threat to competitiveness.  

The wider economy is moving fast. McKinsey’s latest global AI research shows use of AI across functions surged through 2024–25, with generative AI usage now becoming mainstream - meaning your suppliers, media partners and competitors are getting faster and more precise information while many stores are still flying blind. 

In the grocery sector, the hard truth is that retail value is created - and often destroyed - in the physical store, where the vast majority of business is still done by real, physical customers. We obsess over e-commerce conversion while ignoring opportunities for converting the shop floor. If retailers don’t deploy data and AI at the shelf edge and into the hands of associates, they’re not optimising their infrastructure or making use of opportunities to engage with customers where it really matters, and this is where margins are won or lost. 

When they do, these technologies are capable of moving P&L lines in ways that few other innovations can: better availability with computer vision and real-time sensing; price integrity and markdown accuracy with electronic shelf labels (ESLs); more productive labour planning and safer stores; and a measurable new revenue line from retail media that turns first-party data and in-store screens into monetisation rather than a cost centre. Not to mention exciting, emerging shelf-edge technologies that are capable of communicating with shoppers in the moment – a game changer for retailers, shoppers, and brands. 

We are seeing this start to be deployed in earnest. Take pricing and compliance, for example. ESLs stop paper-tag chaos, enable better pricing decisions and accuracy at speed, and turn the shelf itself into a data endpoint. The market isn’t niche anymore: independent estimates put ESL growth in the teens to high-teens CAGR over the rest of the decade, with adoption accelerating in Europe and ramping in the US. The point isn’t the shiny tag; it’s the data exhaust you can utilise - elasticity signals, compliance, promo execution, even waste reduction.  

If you want proof that AI at frontline scale is not only possible but required, watch Walmart. The company isn’t talking about pilots: it’s deploying associate-facing AI for translation, task planning and operations, and publishing an explicit plan to scale AI, gen-AI and AR across the retail stack. The reminder here is uncomfortable: frontline empowerment is the point, not the pilot. 

So where to start? Treat ESLs and computer vision not as gadgets but as a forcing function for connected data on the shop floor. Then get boringly specific about outcomes: on-shelf availability, pricing error rates, markdown leakage, waste, and colleague time returned to service. These are the operational levers that separate sentiment from margin.  

Or look at shopper engagement through hyper personalisation, media and monetisation. Retailers are increasingly using in-store digital advertising to monetise the products, in-aisle. Digital screens on aisles, checkouts and even shopping carts are becoming high-value real estate, while shoppers’ own mobile devices open the door to hyper-personalised engagement in real time. These can potentially drive lucrative new revenue streams. By monetising the data from retail media, retailers benefit from bigger baskets driven by more engaging – potentially more personalised – advertising for consumers. In addition, retail media is the rare flywheel that can fund the hardware. By monetising the data from retail media, your partners and suppliers can also benefit. It becomes a win-win-win, for consumers, retailers and producers.  

Data for data’s sake is no longer what will drive better returns in retail. What matters now is analysing the data that makes a difference, flagging priority tasks to store associates and executing immaculately. That is where the shopfloor becomes so important. Traditional basket and loyalty data analysis allows you to see what choices different types of shoppers have made. Data direct from the shelf opens up a whole new range of possibilities that help you to understand the decision-making processes behind those choices. The winners will be the ones wiring data to where decisions are made and where money changes hands.  

Done right, in store connected digital IoT devices, plus data and AI do far more than just make stores “digital”; it makes them more intelligent, more adaptive and simply more efficient for all. Colleagues get judgment-grade tools; every shelf becomes a sensor and a revenue surface; and you iterate the store daily, not monthly or yearly. Furthermore, customers get a smoother, more enhanced shopping experience that might just be a factor in nudging them to return to your stores, over and over. In this ever-harsher and more competitive market environment, that’s pure retailing gold. 

The brief is simple: connect data to the last metre, govern the tools people are actually using, and evidence proof in the P&L. Modern retail demands real-time insights; data must now operate at the speed of the store.