[E-Daily Reporter Han Jeon-jin ] The use of artificial intelligence (AI) in the retail industry is moving beyond customer service and advertising copywriting to penetrate core operations such as merchandise planning (MD), search, and logistics. AI analyzes thousands of brands to assist MDs in decision-making, identifies products based on customers’ purchase intent, and automatically matches cargo with vehicles. It is establishing itself as a “practical tool” that boosts productivity and drives actual purchases.

According to industry sources on the 6th, major retail and logistics companies—including Lotte Department Store, 11st, and CJ LOGISTICS(000120) —are expanding the scope of AI application across various operational areas. They are rapidly advancing to a stage where AI analyzes the sales, customer, and transportation data accumulated by companies to aid decision-making or perform actual tasks such as search and dispatch. Moving beyond the experimental phase, where the mere adoption of AI was considered significant, these companies are now refining their systems to deliver tangible results in areas such as productivity and sales.

The most notable change is that AI has penetrated areas traditionally reserved for human judgment. Lotte Department Store established and rolled out its in-house “Brand AI” system—which analyzes over 4,000 tenant brands—at the end of last month. By linking previously scattered sales and customer data, the system analyzes brand-specific performance trends and purchase correlations, and uses this information to formulate merchandising (MD) strategies, such as deciding which brands to bring in or remove. In the month following its introduction, the system recorded a 70% repeat-visit rate, and user surveys indicated that productivity had more than doubled compared to similar tasks performed manually.

The role of AI is expanding beyond internal operations to the stage of driving purchases. In July, 11st launched “AI Search,” which analyzes customers’ purchase intent to recommend products. When users search for laptops, the feature suggests keywords based on usage—such as “portable” or “optimized for gaming”—and, once criteria are selected, narrows down the results by considering price, shipping, and reviews. During the month of July, the AI Search’s in-conversion rate (ICVR) was more than twice as high as that of the existing unified search. Specifying purchase criteria at the search stage has effectively increased the rate at which searches lead to actual transactions.

AI is also transforming workflows in the logistics sector, where goods are transported. CJ LOGISTICS’ “The Unban” middle-mile (business-to-business freight) platform uses AI to analyze contracted freight rates, operational history, route-specific demand, cargo characteristics, and regional driver supply and demand to propose transportation solutions and improve vehicle-matching accuracy. The success rate of automated dispatching, which was less than 50% at the service’s launch, has recently risen to over 80%. Additionally, a feature is currently in pilot operation that automatically registers shipping orders when shippers upload Excel files or enter information as if conversing with the AI.

The rapid expansion of AI use in the distribution industry is driven by vast amounts of data. By linking accumulated data—ranging from customers and products to inventory and delivery—with AI, there is significant potential to improve operational efficiency. Across global industries, AI is transitioning from experimentation to operational deployment. According to a survey conducted by consulting firm Deloitte between August and September of last year, which polled 3,235 executives from companies in six industries across 24 countries, 25% of companies had moved more than 40% of their experimental AI projects into operational use. Fifty-four percent predicted they would reach this level within three to six months.

However, the use of AI does not immediately translate into revenue growth. In the same survey, while 66% of companies reported that AI had improved efficiency and productivity, only 20% reported an increase in revenue. Meanwhile, 74% of companies expected AI to boost revenue in the future. Going forward, the gap between retailers is expected to be determined not by the adoption of AI itself, but by how effectively they integrate it into their existing businesses to generate results.

An official in the retail industry stated, “It’s difficult to say that a company is ahead simply because it has adopted AI,” adding, “Ultimately, the difference lies in how well each company tailors the data it has accumulated to actual business operations.” The official continued, “Even when using the same technology, results can vary depending on the specific tasks and on-site practices,” and added, “I expect investment to expand in areas where tangible results are confirmed.”