Home AI Must Play a Role in Making Our Stores Safer

AI Must Play a Role in Making Our Stores Safer

Increasing incidents of violence and aggression in retail spaces and shopping areas demand no shortage of public policy and societal changes. But I believe an AI-fueled technology shift will need to be part of the response. Technology isn’t a panacea to all that is going on, of course. It’s far from it. But technology – and AI specifically – might be the fastest and most realistic action to take that can still alter the trajectory of store violence and give businesses an opportunity to be proactive. And it can have an impact.

The precautions and processes to better ensure the safety of shoppers has never been more important. The issue now has the ear of retail CEOs and its board members. Action needs to follow. In addition to the moral imperative to protect human lives however possible, shopper safety is also a customer experience and reputational issue. Stores considered unsafe, especially if they’re the site of incidents involving weapons, theft, or aggression, will see reduced customer traffic. As with brands’ conscious social responsibility, safety is a top-level issue that speaks to retailers’ customer relationships and core values.

The good news is that startups and technology companies have begun more rapidly building AI-driven applications with unprecedented capabilities for remediating a range of human-threat scenarios. We’re seeing more every month, and there is truly remarkable technology emerging. The promise – and the power – of AI here is to detect and react to threats before it’s too late. Teaming store and parking lot cameras with AI-trained applications to recognize weapons, aggression, and suspicious behaviors gives stores proactive power. And it can save lives.

The importance of physical safety for retailers

Camera-centric security strategies have long been budgeted under loss prevention – but this isn’t that. Rather, the stakes of personal safety demand that emerging AI capabilities play a larger (and public-facing) role in brand conversations. AI has until now been mostly transparent to customers in its ‘traditional’ retail use cases. Stores use AI for handling product recommendations, inventory, predictions, customer counting, etc. But AI-based security can take the spotlight as a feature that provides confidence and assurance to shoppers. Doing so increases both brand trust and store traffic. Strategies in this new and distinct category – call it “threat prevention” – offer stores the opportunity to demonstrate and differentiate themselves as the safest locations for customers to do their shopping – because they are.

The pandemic provides a clear example of the effects that meaningful and visible safety precautions can have on boosting customer traffic. Businesses were able to offer safer customer experiences by providing hand sanitizer, systematically wiping down carts, and installing protective plexiglass. As a result, customers felt the trust and comfort they needed to conduct their business. AI-based shopper safety protections can achieve that same impact on customer perceptions.

An opportunity for real differentiation

This potential for differentiation is analogous to recent shifts in the digital security world. Traditionally, IT security and data privacy have been necessary business expenses with no particularly discernable brand benefit. Companies like Apple are changing this: Apple commercials now promote devices as the best-in-class for keeping personal data private. For example, the fact that iOS automatically strips geolocation data from shared photos is no longer just a safety feature – it’s also a means of winning over customers.

In much the same way, AI will allow businesses to differentiate through safety. I expect we will soon see stores leverage public-facing demonstrations of AI capabilities, coupled with branding that establishes their stores as “the safest place to shop.” Delivering that comfort and security will help earn shoppers’ attention and consideration.

AI approaches to physical threat detection and prevention

The startup space is seeing a surge in new companies specializing in AI threat detection and prevention. This emerging technology area is also seeing rapid growth and acquisitions, as VCs recognize its tremendous potential.

AI-powered retail threat prevention combines security cameras, image recognition, and advanced machine learning algorithms. Success here means identifying weapons, full face-covering masks, aggressive behavior, and other tell-tale indicators of developing threats. This capacity for AI to automatically detect these dangers has already arrived. This is not an AI research challenge. This is now a matter of applying existing AI training models to identify potential threat scenarios that retail spaces can incur. Leveraging security footage, developers are working on AI object detection training for each possible threat context, from weapons themselves to weapons held or worn by subjects, subjects with multiple weapons, subjects within busy crowds, and many more scenarios. The result is AI software with algorithms able to perform accurate and instantaneous threat detection, followed by decisive automated responses.

Take an example where individuals in a store parking lot exit a vehicle carrying concealed guns and knives. Footage from parking lot security cameras is processed by AI software that recognizes these weapons, seeing distinctive signs that a human security officer looking at the feed would not. The AI system activates security protocols. The store locks the door, calls the police, and implements immediate precautions to keep shoppers safe. In this way, AI enables retailers to prevent incidents before they happen.

Better systems, better reputations

Importantly, AI threat prevention is fully capable of enhancing shopper safety for retail brands using the existing security cameras and equipment they’ve already invested in. (Though that said, as retailers naturally upgrade their equipment, adding wireless and IP-based cameras will enable AI applications on top of those cameras to become even more seamless.) Also expect to see AI that take advantage of thermal imaging and other specific capabilities to enter the market for retailers as well, as the threat prevention technology landscape broadens and matures.

Retailers are well-versed in the dynamics of customers avoiding stores with bad reputations. They also understand the draw and comfort of locations with more prestige and trust. AI-based shopper safety is now at a very early stage, but as startups and other companies introduce nascent technology, retailer adoption is going to unfold quickly. By their nature, AI applications in this space should be able to scale rapidly. And demand will likely require that, as retailers compete to offer reassurance and provable safety measures for their shoppers.

About ReadWrite’s Editorial Process

The ReadWrite Editorial policy involves closely monitoring the tech industry for major developments, new product launches, AI breakthroughs, video game releases and other newsworthy events. Editors assign relevant stories to staff writers or freelance contributors with expertise in each particular topic area. Before publication, articles go through a rigorous round of editing for accuracy, clarity, and to ensure adherence to ReadWrite's style guidelines.

Shomron Jacob
Engineering Manager, Applied Machine Learning and AI

Shomron Jacob is an Engineering Manager focused on Applied Machine Learning and AI at Iterate.ai, creator of the Interplay low-code platform for rapidly prototyping AI-based applications across industries. Shomron began his career as a software engineer but soon found himself learning ML/AI, and switched his professional direction to follow it. He lives in Silicon Valley.

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