For every newly introduced security system, criminals seem to respond with more sophisticated workarounds. Theft has always been the greatest cause of shrinkage for retailers. But in recent years, the problem has grown exponentially, such that retailers are reporting nearly $100 billion in annual losses due to theft. As the cycle continues, stores are trying to get smarter than the thieves, by using their resources to solicit, design, and install anti-theft technology throughout their supply chains.

Many big box retailers, such as Lowe’s, require the manufacturers with which they have supply relationships to embed radio frequency identification (RFID) chips into their products during the manufacturing process. This addition not only helps them combat the theft of high-priced items, such as power tools, but also enables them to track inventory as it moves through each step of the supply chain. Relying on RFID chips requires the stores to install monitors at the exits, to alert store employees when someone leaves without paying.

Another form of monitoring instead leverages AI monitors at self-checkout points, to observe shoppers who might be tempted to engage in theft as they scan their own items. Walmart’s anti-theft systems capture the size and mass of products being scanned and bagged; they also alert store staff if the wrong item has been scanned. For example, if a sneaky shopper swapped the stickers on their fruit, such that they scanned the bar code for a cantaloupe but actually took a more expensive pineapple, the monitor should be able to detect the different shape and raise an alert.

In these roles, AI helps retailers manage potential theft more efficiently. Rather than having to hire a worker to observe every self-checkout line, Walmart can make the one-time investment in technology and achieve similar monitoring capabilities. In addition, AI arguably is more objective. Its use of algorithms that focus on products purchased should reduce the risk of implicit bias by sales associates, such as due to a shopper’s physical appearance.

Moreover, AI can track patterns of suspicious behavior and thereby alert stores to the risk of an ongoing theft in real-time. Some of the advanced technologies supporting these efforts include RFID heat maps and autonomous security tools in the store. In addition, license plate readers in parking lots can give law enforcement information to pursue criminals if the retailer chooses to avoid having store personnel confront the criminals directly. These readers also can track repeat visits by vehicles, which the retailer can use to cross-check against reports of theft. If the same vehicle is repeatedly in the parking lot on the same days that thefts occur, the owner of that car represents a potential suspect.

Still, the integration of these advanced technologies raises the potential for long-term risks. Many customers already voice their concerns about invasive technology, citing their right to privacy in stores and parking lots. Furthermore, consumer advocates have noted the distinct lack of transparency by retailers regarding how customers are being monitored and how the retailers are using these collected tracking data. Experts warn retailers to carefully plan their announcement and implementation of new anti-theft devices, to avoid significant backlash. Once a retailer gathers personally identifiable data, such as through facial recognition software or monitors that track biodata, it must be responsible for protecting those data too. Otherwise, in trying to protect itself from the risk of retail theft, it puts its own shoppers at risk of identity theft.

Discussion Questions

1. As a consumer, do you feel comfortable with the implementation of the described anti-theft technologies? Why or why not?
2. Describe a recent retail experience you’ve had. Identify one potential supply-side pain point observed, and explain how the implementation of one of the anti-theft devices could alleviate this problem.

Sources: Bob Woods, “How America’s Biggest Retailers Plan to Use Technology to Catch Organized Retail Theft,” CNBC, July 29, 2023; Lily Lopate, “NRF 2023: How AI Is Helping Retailers with Loss Prevention,” BizTech Magazine, January 23, 2023; OpenAI ChatGPT, “Assistance with Research on Anti-Theft Technologies in Retail,” April 22, 2024; Sharon Hong, “4 Technology Solutions for Deterring Retail Theft,” ASIS Online, December 11, 2023.