If you were asked to write a business case for AI in retail, you wouldn’t need to search very far for some serious stats to bolster your proposal.

Retailers that fully embrace AI typically enjoy a 7% uplift in sales. AI will save retailers $340 billion annually. Shoppers that use AI as part of their purchasing journey spend 53% more per visit and have a 60% higher conversion rate.

At this stage, you probably don’t need any more evangelizing about the potential of AI in retail. You probably don’t need to hear much more about how it will transform shopping journeys and retail operations, either, even for physical stores. We wrote about some of the need-to-know implications of AI for physical retail and POS systems in this article, covering the likes of personalization at checkout, smart inventory management and merchandising, and labor optimization.

But for all these ‘opportunities’, retailers still ask us a fundamental question: how do we make all of this happen? For all the hype around AI, from our perspective as retail tech specialists, a lot more needs to be done to help retailers understand the practical nuts and bolts of AI adoption. That need is especially acute when it comes to hardware.

All too often, AI gets talked about as purely a software play. Software may supply the intelligence, but it cannot work alone. Retailers also need hardware capable of running the algorithms, collecting and processing data quickly, and turning decisions into action.

With that in mind, we’ve put together this introductory guide to what should be on your POS shopping list if you want to embrace AI in your store.

1. An AI-Capable POS Terminal

AI applications can require a lot more processing power. So if you’re still running legacy checkout  terminals, the first item on your shopping list will be to upgrade to modern units with multi-core processors, adequate memory and fast solid-state storage. While retailers typically try to get the longest lifespan possible out of POS hardware to maximize ROI, 67% of high-performing businesses say they have prioritized upgrades in 2026, a sure sign of how AI requirements are shaping investment.

2. Cameras, Scanners and Sensors

AI feeds off data. If you want AI to do all the really clever stuff in your store like personalize promotional displays in real time or provide smart merchandising forecasts in close to real time, you need a lot of relevant data. Your standard POS transaction streams are important. But the real game-changer comes when you can feed your AI ambient data about what’s happening in your store.

This is achieved using cameras, RFID readers, and various types of on-shelf sensors. The idea is to track customer and product movements, and use that information to make decisions. Beyond marketing and merchandising, AI-powered surveillance systems are playing an increasingly important role in store security by identifying suspicious patterns or behavior and cross-referencing what customers take off shelves against what gets processed through POS.

3. In-Store Edge Computing

Most retail POS systems run in the cloud these days. But that creates an issue if you want to add in AI capabilities. Sending the large volumes of data AI relies on back and forth to a cloud datacenter eats up network bandwidth and can introduce latency – delays in outputs that can dampen the benefits of getting real-time insights and automated responses.

Edge computing infrastructure allows data to be processed on the premises, close to where it is generated. This allows for faster responses, but it also makes critical functions less reliant on network performance.

4. Reliable Network Infrastructure

Even with edge servers to support the data processing load, AI-ready POS systems still need reliable connectivity that can stand up to the extra demands AI places on the network. As well as getting the speed and bandwidth right, stores need to think carefully about router placement and how devices connect. For the more critical hardware endpoints, wired ethernet connections are more reliable than WiFi.

It’s also important to separate POS, IoT and guest traffic into separate streams for both security and performance reasons. And you should consider back-up network options to avoid your whole POS system going down if there’s an outage.

5. Hardware That Turns Insight Into Action

Finally, AI only creates value when an employee, customer or system can act on its output. AI can do a lot behind the scenes controlling intelligent automation within software-led processes. But if you want customers and personnel to respond to AI recommendations, you need an interface.

Customer-facing displays and kiosk touchscreens can present recommendations and loyalty offers. POS screens and mobile POS devices can provide tailored service scripts to employees, provide inventory updates or issue security alerts. Electronic shelf labels can implement pricing changes, while digital signage can adapt content to local contexts.

Start With the Use Case

The five steps we’ve outlined create a complete hardware chain for AI-ready POS: devices that collect data, a blend of local and cloud infrastructure that processes and interprets it, and endpoints that communicate or carry out the response.

The specifics of how this pans out will vary with every retailer and every store. It’s unrealistic to expect to complete a full AI-ready roll-out in a single project. The smartest approach is to start with a defined operational goal, focus on what you need to achieve it, and when you have a proven capability in place, build from there.

By choosing modular, commercial-grade hardware, retailers can create a POS platform that not only supports today’s AI applications, but is future-ready for whatever new possibilities this fast-moving field opens up going forward.

To find out more about starting your AI POS journey, contact the RTG team today.