According to a research report from Orient Securities, AI is expected to evolve from a point-based tool to a full-chain data-driven solution, unlocking greater potential. The duty-free industry is viewed favorably for accelerating AI adoption, with the future focus shifting from improving node efficiency to enhancing full-chain turnover and precision operational capabilities. However, the pace of adoption depends on data quality, system integration levels, and the standardization depth of business scenarios. The main viewpoints of Orient Securities are as follows:

Since the second half of 2025, the duty-free industry has accelerated the implementation of AI, primarily focusing on supply chain management, front-end sales, and internal digital intelligence operations. In July 2025, the Hainan Provincial Department of Commerce reported that Haikou Customs implemented AI-powered smart supervision models, such as "remote localized inspection," for Hainan offshore duty-free goods inspections. This reduced the inspection time for a single batch of duty-free cosmetics to 20 minutes, saving approximately 1.4 days per batch compared to traditional methods. In August 2025, China Duty-Free Group publicly tendered for an "AI Large Model Construction Project - Shopping Assistant," aimed at starting online and gradually covering all offline scenarios to build a multimodal interactive shopping hub spanning pre-sale, in-sale, and post-sale processes. Volcanic Engine won the bid with a value of 1.83 million yuan. Zhuhai Duty-Free Group disclosed in its interim report for 2025 that it had deployed an AI passenger flow analysis system to optimize display and inventory dynamically. In November 2025, following the establishment of a joint digital operation system with Seeyon, Shenzhen Duty-Free Group leveraged its advanced AI-COP intelligent collaborative operation platform to achieve minute-level updates for capital flow and sales data. Process handling time was reduced by over 50%, automated rate for expense accounting exceeded 90%, manual intervention decreased by 50%, financial error rates dropped by 90%, employee operational efficiency improved by 40%, and process compliance risks fell by 90%. These advancements help duty-free operators enhance operational turnover, reduce costs, and strengthen service capabilities.

In the future, AI applications in the duty-free industry are expected to extend from point-based efficiency tools to full-chain data-driven solutions, offering substantial growth potential. In the short term, AI will concentrate on standardized scenarios with substantial data accumulation, such as customer service guidance, warehouse sorting, staff scheduling, passenger flow analysis, and financial forecasting, continuing to free up human resources and improve turnover efficiency. In the medium term, as industry data accumulates and model capabilities strengthen, duty-free AI is anticipated to evolve into a full-journey intelligent system covering "pre-trip, during-trip, and post-trip" phases. By utilizing digital identity, seamless payment, and automated fulfillment, friction points like queuing and verification can be minimized. Intelligent recommendations will enhance throughput and conversion rates during peak hours, boosting average transaction value and repurchase efficiency. This will shift offline store operations from "experience-driven" to "data-driven," enabling more precise display, inventory, and service allocation capabilities. In the medium to long term, AI-driven demand forecasting combined with intelligent product selection, smart replenishment, and supply chain risk alerts, along with dynamic pricing, will assist duty-free enterprises in achieving optimal product assortment matching, inventory health, and gross margin management within the context of a "buyer system" refined supply chain and fluctuating demand. Simultaneously, it will promote duty-free channels as frontier platforms for the early incubation and validation of new product categories and consumer trends.

Risks include a slower-than-expected recovery in the macroeconomy and household income, which could suppress discretionary consumption and travel demand; slower-than-anticipated iteration and implementation of AI; and increased volatility in overall market valuations, posing risks of periodic adjustments for the sector.