Of all the technologies on the modern retail map, AI (what else?) stands out as the most talked about and most hyped. And as businesses pursue the dream of the intelligent store – digitized, data-driven environments where information is harvested to improve the customer experience – IoT technology is very much back in vogue, too.

Connected networks of sensors and cameras do the data gathering. AI tools do the analytics and activation. A recent study found that 49% of retail and hospitality chains are investing in IoT sensors purely for product quality and safety monitoring purposes. While 48% have implemented AI demand forecasting solutions to help with inventory and labor planning.

Yet there’s a third technology in the make up of intelligent stores that maybe needs teasing out of the shadows a little. Edge computing. It’s one of those things that everyone has heard about but are a little slower adopting. The same survey found 91% of retailers think edge computing is important. But total current adoption stands a little over 50%.

But this gap between recognition and action could be holding up the smart store revolution. Here’s why edge solutions should be on your store transformation priority list.

What is edge computing?

Edge computing involves the use of local servers to process data ‘at the network edge’, or close to where it is gathered and activated – in this case, in or around the store.

This isn’t an about turn away from cloud-based computing back to legacy on-premise systems. Edge servers aren’t meant to provide the full range of compute resources you need to run your POS and all associated software. That can still be done remotely at a data centre, with all the benefits of resource efficiency, scale and cost we know that brings.

Instead, edge computing is about augmenting cloud-based systems in one particular way – allowing critical data processing to take place close to where that data needs to be used. This slashes latency compared to sending it potentially hundreds of miles back and forth to a remote data centre. Or to put it another way, edge computing makes data processing faster. And when you’re collecting large volumes of data from cameras, sensors and other devices, and running resource-intensive AI tools to analyze it all, that extra speed is critical for the kind of real-time outputs you want when aiming for a truly responsive and proactive digitized store experience.

Think of it like this. If IoT devices are a store’s eyes and ears. And AI is its cognitive functions. Edge servers are the brain where data gets turned into decisions.

How edge computing powers intelligent stores

Stores are fast-moving, dynamic environments. And optimizing the in-store experience is a game of fine margins. Customers move quickly, shelves empty unexpectedly, queues form without warning. Small gains in the speed and efficiency with which you respond to real-time scenarios quickly multiply into something significant.

Digitization and data have radically transformed retailers’ abilities to understand what is happening across a store at any one moment. Shortening the path from insight to action through the use of edge servers running powerful AI algorithms is the icing on the cake. This is often referred to as ‘edge AI’.

Some applications of edge AI in retail include:

• Loss prevention and shrink reduction: By analysing video and transaction data locally, edge systems can spot incidents of theft, scanning errors, or process breakdowns in real time. This gives staff an opportunity to intervene in the moment and prevent losses, rather than reviewing procedures after the fact.
• Inventory management: With the extra speed of edge computing, smart shelf systems tracking availability, stock-outs, promotional compliance etc become more agile and efficient. Faster intelligence means faster replenishment, fewer missed sales, and increased customer satisfaction.
• Merchandising optimization: Cameras and sensors track footfall and browse times at displays around a store, providing invaluable information about product placement and the impact of promotions.
• Service optimization: More and more retailers are using cameras to monitor queues and to pick up signs that customers need assistance. Real-time processing means staff can be redeployed exactly when and where they are needed.

For retailers investing in cutting-edge integrated POS systems, sensors, and AI-driven analytics, edge infrastructure is no longer a nice-to-have. The speed, reliability and agility local processing capabilities provide in increasingly data saturated environments is what will give your evolution towards smarter operations a hidden edge.