AI and Edge Computing Bring Amazing Benefits to Retail

There is some negative press surrounding topics like automation, robotics, artificial intelligence, and edge computing. Old rhetoric states that adopting these technologies will take away jobs from people who need them while compromising service and experience, especially in customer-facing industries like retail.

Artificial intelligence and edge computing might sound like complex technology out of reach of most retail companies, but that couldn’t be further from the truth. How can AI and edge computing technology provide benefits to retail?

Defining Edge Computing

Even those familiar with artificial intelligence and machine learning might not have heard the term “edge computing.” Many of these networks rely on cloud computing – sending information to the digital cloud to reduce the need for on-site storage. It’s practical, but needing to transmit data to and from the cloud can introduce the potential for latency that interferes with workplace efficiency.

Experts define edge computing as “a distributed computing framework that brings enterprise applications closer to data sources such as IoT devices or local edge servers.” In simplified terms, it removes the need to send data to the cloud by keeping everything – storage, processing, and all other associated hardware and software processes – on-site.

How can AI and edge computing add to the benefits of retail technology?

Putting Data to Good Use

The retail industry generates upwards of 40 petabytes of data every hour. Much of this information goes unused, collecting digital dust on hard drives or in the cloud because companies don’t have the software or knowledge necessary to make the most of it.

Combining AI and edge computing can make it easier for companies to sort through this massive data collection, separating the digital wheat from chaff. From there, these systems can look for patterns, monitor trends, and predict consumer behaviors.

These predictions are based on pattern recognition rather than any fortune-telling. AI systems can tell the future by looking at the past because consumer trends and behaviors often repeat themselves. Some external variables may impact these predictions – such as natural disasters, a global pandemic, or unprecedented inflation – but for the most part, once a pattern is established, humans are creatures of habit and rarely deviate from them.

Relying on edge computing systems rather than cloud computing prevents upload and download latency from interfering with the accuracy of these predictions.
From Manufacturing to Storefront

Edge computing and AI might seem like technology best suited for customer-facing settings, but it has applications throughout the retail industry.

In the manufacturing stage, robotic inspection technologies can reduce the number of errors that make their way into customers’ hands while reducing the number of working hours necessary to complete these tasks. When exploring the logistics facets of the industry, AI and edge computing can help increase productivity and minimize manual processes while assisting companies in achieving deliveries faster than ever.

Edge computing in each facility can help keep processes closer to home, making it easier to meet deadlines. The two technologies are not mutually exclusive. An edge computing system can be synced with the cloud as well, creating a valuable complementary service that helps keep everyone involved on the same page.

Creating the Checkout-Free Retail Experience

One of the most familiar parts of the retail experience is the checkout process. Consumers bring their purchases to trained cashiers or, in some cases, to a self-checkout station. From there, shoppers can scan their choices and pay for them before exiting the store.

Companies like Amazon are considering ways to do away with this experience altogether in favor of the checkout-free store. Instead of scanning their purchases, shoppers simply pick up what they need. Cameras or sensors total the purchase and automatically deduct the amount from the debit or credit card attached to the shopper’s account. There’s no need for cashiers or even self-checkout stations.

Real-time AI feeds an essential part of the success of these pilot programs. AI programs need to detect and identify each shopper and correctly identify each item they’ve picked up to purchase. These AI feeds need to be able to complete these tasks in real time.

The 100-millisecond latency time associated with cloud computing might not seem like much. Still, compared to edge computing latency of fewer than 5 milliseconds, it might as well be an eternity.

Building the Future of Retail

The retail industry may be shifting its focus to e-commerce, but don’t underestimate the importance of physical storefronts. The shift to a checkout-free shopping experience is just one way that retailers adapt to this change. As the retail industry adopts new technologies, there will be an increased demand for fast and lag-free processing power.

Cloud computing was once considered the perfect solution because it didn’t rely on physical data storage technologies. Still, even with a fast internet connection, cloud systems can’t compete with the almost nonexistent latency offered by edge computing. When exploring the benefits of retail technology, it’s essential not to overlook edge computing and its varied uses.

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