Businesses across industries are currently exploring the ways AI can improve productivity and user experiences, and that includes retailers. An August 2023 report estimated that retailers would spend upwards of $7 billion on AI-enabled tools this year—and predicts that number will explode to nearly $30 billion by 2028. It’s clear that retail is on the precipice of yet another large-scale shift, this time driven by innovation rather than necessity (as was the case during the COVID-19 years).
As we enter this time of immense growth, change, and progress, here’s what consumers and retailers might expect from AI-driven operations in the coming year:
Stronger loss prevention and safety programs
Mitigating losses due to theft and fraud has long served as the jumping-off point for progress in retail tech, and it remains central to the industry’s progress today. AI’s potential to address rising retail crime rates will no doubt be a primary driver of adoption in the coming year.
Computer vision, predictive analytics, and other AI-powered tools already help retailers take a more proactive approach to loss prevention programs, and the efficacy of these models will likely grow in the coming year. The data gathered by all their systems can highlight patterns related to thieves' tactics, at-risk items, and other details that are specific to each store’s layout and inventory to harden targets. These insights can also teach ML models what to “look for” on the floor in the lead-up to organized retail crime events so workers, customers, and leaders are not caught off-guard.
Enhanced supply chain operations
AI-powered predictive analytics suites are also likely to improve, helping retailers forecast traffic, sales, and other metrics more accurately. Advanced AI can turn radio-frequency ID tracking into data to uncover patterns, opening a whole new world of optimization to retailers.
Using these insights, predictive AI platforms can anticipate out-of-stocks, alert associates to potential supply chain problems before they happen, inform leaders about underperforming merchandise, and more. As computing power rises and datasets expand, these plans will get more precise, driving more thoughtful promotional designs, better merchandising programs, and reduced losses due to waste.
Higher employee satisfaction
Keeping stores staffed is increasingly difficult for retailers worldwide. The U.S., the U.K., Canada, Italy, Japan, and many more countries are facing an ongoing labor shortage, meaning that initiatives that help retailers retain personnel are quickly becoming the most important part of labor strategies. AI tools are likely to be critical to these efforts, as they can improve employees’ work lives significantly, leading to higher job satisfaction and retention levels.
Shopper intelligence helps associates better understand how to serve customers and anticipate needs, while insights from retailers' complete connected suites can inform staffing models to help leaders plan for lulls and rushes. That means they always have the right number of people for the job so no one is bored or stretched too thin. Furthermore, an improved supply chain makes day-to-day tasks more pleasant and more effective loss prevention will help employees feel safer on the job amid growing concerns about hostility in frontline businesses.
Improved customer experiences
All of the above will no doubt make shopping more satisfying for customers, but that’s far from the end of the road for AI-led customer experience improvements. Retailers are already using Gen AI and NLP to improve their “phygital” (the term many are using to describe hybrid shopping models) offerings. Walmart, for example, plans to launch a shopping assistant chatbot that can discuss a customer’s needs with them to identify the product that best meets their needs and help them find a store that has the item in stock.
Though computer vision’s power to make stores safer is certainly a plus for shoppers, it can also help personalize and streamline their journeys. AI-enabled systems can record shopper demographic and preference information as data points to be correlated, cross-referenced, and analyzed.
When these data sets come together, they highlight opportunities for retailers to shape customer experiences for specific regions, cities, and even stores and departments. As facial recognition tools become more common and reliable, it’s possible that stores could even use them to design hyper-personalized experiences for specific customers.
Possibilities and progress
No one can say precisely what the coming years will bring, but we can be certain that AI’s impact on retail will be profound. As 2023 comes to an end and the discussion around the technology continues, retailers that have not yet started thinking about the role AI will play in their plans may want to begin the process. Doing so thoughtfully and early may set them on course to help define what comes next and contribute to the ongoing story of retail’s evolution.