The Future of Smart Retail

AI, IoT, and Edge Computing: The Future of Smart Retail

March 3, 2025

Christina Cardoza

A woman grocery store employee in the kitchen supply aisle looking over data on a tablet.

Retailers have always valued data—collected, analyzed, and implemented it to keep abreast of their customers’ wants and needs. But in times past, they had to wait until the end of the quarter or the end of the year to crunch those numbers and see which way the wind was blowing. It’s pretty clear that consumer trends move much too fast nowadays for that kind of cycle to be useful.

AI, computer vision, and edge computing—these technologies have stepped in to make data processing much more efficient. And that’s not all: They are also involved in retail solutions that can affect everything from controlling inventory to turning mundane jobs into more valuable and fulfilling positions.

We explore some of these solutions in the world of smart retail with Silvia Kuo, Business Development Director for the EMEA region at computer-hardware enterprise company ASUS. She guides us through the challenges retailers face, the importance of IoT partnerships to the solutions, and the role that technologies like AI play in changing the way we shop (Video 1).

Video 1. Silvia Kuo from ASUS talks about the latest smart retail opportunities and technologies. (Source: insight.tech)

What challenges do businesses face in getting to smart retail?

Smart retail has been around for a while, and everyone’s been talking about it. Of course, as with any change, there’s also a bit of resistance. There’s a lot of innovation and adoption happening, but I think the industry has probably been looking for a direction. I think that a few years from now, retail might look a bit different from how we know it today.

For example, logistics—there’s a lot that we can do with logistics. Sometimes today the process is still very manual, things like tracking the stock when it comes in. So instead of sending someone to count it, you can have a system that can just do it for you very quickly. You can also have an alerting system that lets you restock quickly without having to send someone to see if the shelves are empty.

Or space optimization. Now with computer vision we can look at the whole store and see a heat map of which areas people visit the most—because of the layout or maybe because of the brand you put there. And with this knowledge you can, for example, move the best brands during the high season in Q4, or you can adjust the rent or the fees for a vendor.

One of the main challenges retailers are dealing with is a lack of personnel—people not wanting to do these kinds of operational, routine jobs. Retailers are quite desperate to find solutions that are not too costly and that will create jobs that are more meaningful. So instead of filling up the shelves, people will be managing systems that will fill up the shelves for them. Or instead of asking, “What do I need to buy for the next quarter?” and completing an Excel form, they can analyze it through a computer and make a final decision or just review it.

This kind of management of systems is where we see that the industry is going. A lot of people feel that AI is going to be a threat and replace all of our jobs. But I think that it’s a shift, and it can improve people’s lives.

What is the role of advanced technologies like AI in this transformation?

In retail the things we do always fall into two categories: Either it is gathering data to analyze it for making data-driven decisions, or it is automating process. AI, computer vision, edge computing—they are all technologies behind something; it’s more of a horizontal. For example, AI can help with the engagement of customers, because nowadays we see that stores are not really a place just to purchase but more of a customer-experience or brand-experience space.

We have seen other things like digital signage targeting an audience. You can instantly show a group of people something that is targeted to them, or you can even be interactive and ask them questions. This is what AI is doing now: interacting with customers, analyzing a situation in real time behind the scenes, and giving feedback. In the past you had data, but you didn’t always know what to do with it. Now you can understand what the behavior of your audience is in one district in the country as opposed to another, and adjust, say, the stock according to that analysis.

Computer vision is also a horizontal technology—for example, for recycling. A lot of retail grocery stores have recycling machines, and the technology can determine what kind of empty product is being put into the machine. In some cases, in Europe, they give money back, so you can spend it in the store.

How do ASUS solutions avoid siloing?

ASUS has a comprehensive, holistic type of approach, because that’s the nature of a computer company, right? We are the brain, let’s say, and behind all of this innovation is where we run. So when we are looking into a problem, we have to look at the solution as a whole and then see what components to put into that solution to solve the problem.

What type of infrastructure or investment is necessary to start?

We always try to use what is there, like the cameras that are already doing security. But we adjust them to use that same video stream for analysis on the edge computer afterward. So we reuse these kinds of things. Of course there is some investment involved, because it’s a technology that wasn’t there before—some sensors or some cameras that have certain different angles or some signage to communicate with the customer—and these are investments that have to be made.

A new technology such as AI needs a lot of computers, but many times stores have their own little data centers. We can collect the data on the edge, in the stores, and pull it back to these little data centers where all the analysis and decision-making can happen. As much as we can, we try to reuse.

Can you share some use cases of businesses leveraging these solutions?

I have two examples: one that is more about problem-solving and another one that is more of an enhancement. The first one was this grocery retailer that was looking for an automated way to alert them of empty shelves—especially in the fresh-produce area, because it was a very manual process there. They also wanted to combine that with a way to adjust pricing throughout the day depending on the performance of each product.

We used computer vision to first identify the produce that was there. Throughout the day at certain intervals it would take different images and do some analysis to determine the level of stock. Then this would create alerts in the central system, and also all of the operators would see those alerts and know: “I have to refill the apples and the oranges now.”

Based on the same AI technology of recognition of the product, we also automated the pricing. So if, for example, the apples were not selling very well on one particular day and at 4:00 they wanted to start clearing them, they could automatically change the e-tags below the apples, changing the information and the price.

The second example is more about enhancement and improving understanding of the customer. This was a technology that we developed together with a software vendor of ours in France. It involved putting a sensor and a camera out with certain products to understand how people interacted with them.

This solution was looking at things like: How long do customers stand in front of the brand? Which products do they pick up? How long do they interact with the product? Did they buy it or put it back? So there was a lot of data accumulated there, and the vendor got a lot of interest from the brands themselves, because brands want to understand, when they launch a new product, how people like it.

What is the value to ASUS of its technology partnerships?

Intel has been a long-term partner to ASUS. This relationship was really crucial when the IoT department was created. Intel is also very supportive to its partners, for example, engaging us with the end customers. Many of the customers in the examples I gave earlier were actually people that Intel introduced us to. And when Intel is developing something for AI, it is using OpenVINO^™ to implement these new features, and ASUS is asked to be a tester of those features. In many cases, we are one of the first to try out new Intel technology, so we’re able to implement it in a lot of the new products that we launch.

We also market the features and solutions out there. There are lots of choices of technology, and we offer different kinds, but when we see a company like Intel coming into this space and trying to optimize and democratize it—because it’s not just about selling more computers but about how you make it accessible to people—we want to support that.

Regarding the partner program that we run ourselves at ASUS, I always say that in IoT it’s very difficult to do something on your own. There are so many components, right? We see camera makers; they are optimizing their software to make AI more possible or trying to put chips on their cameras so that it’s easier for the edge computer to analyze more data. Everybody understands this: It’s hard to do everything alone, so you need partnerships.

Where do you think smart retail is going from here?

It’s a broad question, but I will try to guess. I think one thing is that, as I said before, we will see a lot more automation of operations and also people having more meaningful roles, more interesting jobs. Another thing is a lot of interactive devices and kiosks, and AI will help with this and with the problem of having enough staff to attend to all of the guests. We are seeing a lot of voice AI that is very accurate and that even has accents and slang.

Also, I think that a lot of retail spaces will be become showrooms, really; they won’t just be places to buy things. And I would even dare to say that in some of these spaces you would just place orders and have them shipped to your home; you won’t even have to wait for the clerk. They will be more of a showroom, a tryout room.

Sometimes in Asia there’s this obsession for making things faster and more seamless, right? And I think that will be something that will expand across the world, making experiences more seamless and having a nice experience instead of having to wait.