Orient: Tax-free industry digitization and AI application accelerate implementation, reducing costs and improving efficiency while simultaneously reconstructing the experience.

Orient released a research report stating that in the future, AI is expected to extend from a single-point tool to a full-chain data-driven model, unlocking greater potential. There is optimism for the accelerated application of AI in the duty-free industry, gradually upgrading from "node efficiency improvement" to "full-chain turnover and precise operational capabilities", but the pace depends on the quality of data, degree of system integration, and depth of standardization of business scenarios. Key points highlighted by Orient are as follows: Since the second half of 2025, the duty-free industry has accelerated the implementation of AI, focusing on supply chain, front-end sales, and internal digital operations. In July 2025, the Hainan Provincial Department of Commerce website reported that Haikou Customs in Hainan's offshore duty-free product inspections implemented an "remote territorial inspection" AI intelligent supervision model, reducing the inspection time for a batch of duty-free cosmetics to 20 minutes, saving approximately 1.4 days per batch compared to traditional methods. In August 2025, China Tourism Group Duty Free Corporation publicly tendered for the "AI large model construction project - shopping assistant", aiming to gradually cover offline scenarios starting from online, building a multi-modal interactive shopping hub covering pre-sales, in-sale, and post-sale, with a bid amount of 1,830,000 RMB. Zhuhai Zhumian Group disclosed the deployment of AI customer flow analysis system dynamics in the 2025 interim report to optimize display and inventory. In November 2025, Shenzhen Duty-Free Group and Beijing Seeyon Internet Software Corp. jointly built a digital operation system, relying on its leading AI-COP intelligent collaborative operation platform, enabling real-time updates of fund flows and sales data at the minute level, reducing process handling time by over 50%, automating cost accounting by over 90%, reducing manual intervention by 50%, decreasing financial error rates by 90%, improving employee operating efficiency by 40%, and reducing process compliance risks by 90%. All of these measures help duty-free businesses improve operational turnover, reduce costs, and enhance service capabilities. In the future, AI applications in the duty-free industry are expected to extend from single-point efficiency tools to full-chain data-driven models, offering vast potential. In the short term, AI will focus more on standardized scenarios with substantial data accumulation, such as customer service guidance, warehouse sorting, scheduling, customer flow analysis, and financial forecasting, continuing to release manpower and improve turnover efficiency. In the medium term, with the accumulation of industry data and enhanced modeling capabilities, duty-free AI is expected to evolve into a full journey intelligence system covering "pre-trip, during-trip, and post-trip"; leveraging digital identity, contactless payments, and automated fulfilment to reduce queuing and verification frictions; through intelligent recommendations, increase peak throughput and conversion rates, improve customer spend and repeat purchase efficiency. Gradually transitioning offline store operations from "experience-driven" to "data-driven", forming more precise display, inventory, and service configuration capabilities. In the medium to long term, AI-driven demand forecasting + intelligent selection, intelligent replenishment + supply chain risk warning, dynamic pricing, will help duty-free enterprises achieve better matching of product offerings, healthy inventory levels, and profit control in a "buyer-oriented" selected supply chain and volatile demand environment, meanwhile promote duty-free channels to become a leading edge scenario for early incubation and validation of new product categories/new consumption trends. Risk warning: Macro-economic and household income recovery below expectations, or suppression of optional consumer and travel demands; AI iteration landing slower than expected; increased market valuation fluctuations, with sector-specific adjustment risks.