Artificial intelligence is moving beyond analytics and experimental pilots into routine workflows across retail outlets in the Asia\u2011Pacific region, a trend highlighted by a Q4 2025 survey conducted by GlobalData. The study found that 45\u202fpercent of consumers in Asia and Australasia are very or quite likely to purchase a product after receiving an AI recommendation or endorsement, underscoring the growing influence of machine\u2011learning systems on shopping behaviour.<\/p>\n
Jaya Dandey, a consumer analyst at GlobalData, noted that machine\u2011learning algorithms have long guided when retailers encourage purchases, which products are displayed, and which discounts are offered. \u201cNow, agentic systems can also complete shopping\u2011related tasks end\u2011to\u2011end,\u201d she said, indicating a shift toward more autonomous AI solutions that manage entire customer journeys.<\/p>\n
Retailers in the region are experimenting with computer vision and machine\u2011learning technologies to streamline operations. In Japan, Lawson launched its AI\u2011enabled \u201cLawson Go\u201d stores in 2022. The retailer partnered with CloudPick in 2025 to integrate AI, machine\u2011learning, and computer\u2011vision capabilities, resulting in the removal of checkout lines and cashiers and an improved customer experience.<\/p>\n
South Korea\u2019s Fainders.AI introduced a compact, cashier\u2011less MicroStore inside a gym in 2024, demonstrating the feasibility of autonomous retail in diverse business settings. These deployments illustrate how AI can reduce the need for human staff in high\u2011traffic, small\u2011footprint stores.<\/p>\n
AI also supports forecasting and automation of retail replenishment, a capability that is particularly valuable in the APAC market where store footprints are small and replenishment frequency is high. Japanese food\u2011retail chain Coop Sapporo uses a camera\u2011based AI system called Sora\u2011cam, developed by Soracom, to monitor shelf stock levels. The system helps the chain avoid overstocking, reduce unsold merchandise, and alerts staff to apply discount labels to items nearing expiry. An analytics team evaluates the images generated by Sora\u2011cam to determine optimal shelf display ratios and to track waste and markdown timing, thereby improving promotion efficiency. In Southeast Asian markets, where price sensitivity is high, even modest gains in promotion efficiency can increase profit margins.<\/p>\n
AI\u2011driven labour optimisation measures\u2014such as scheduling, task priority lists, and workload balancing\u2014assist retailers in Japan and South Korea, which face structural labour shortages, and also provide efficiency benefits in rapidly growing Southeast Asian markets.<\/p>\n
Agentic AI refers to systems that can understand a goal, plan steps, stay within budget or allergen constraints, execute actions across multiple platforms, ask clarifying questions, and learn preferences over time. Dandey explained that in food retail, such systems can allow customers to bypass individual item searches by simply stating their overall intent. For example, a shopper might ask an AI agent to \u201cplan five dinners for a family of four, mostly Asian recipes, no shellfish, under 45 minutes.\u201d The agent would then generate recipes, build a shopping cart, size quantities, and add missing staples.<\/p>\n
These capabilities align with regional shopping habits, as many APAC households cook frequently and purchase fresh ingredients. AI agents that recognise local cuisines\u2014such as Korean banchan, Japanese bentos, and Indian spice bases\u2014are better suited to regional preferences than generic Western meal plans. Dandey added that in many APAC markets, shopping is already deeply integrated with digital wallets, messaging apps, ride\u2011hailing, and delivery ecosystems, making it easier for agentic AI to plug into daily routines.<\/p>\n
Despite the promise, several challenges remain. Ensuring private data sharing consent, minimising hallucinations related to allergens and ingredients, and implementing proper localisation with language nuance are critical hurdles that must be addressed before widespread adoption.<\/p>\n
Retailers across the Asia\u2011Pacific are expected to continue integrating AI into core operations over the next few years. As more companies deploy computer\u2011vision\u2011enabled checkout systems and agentic shopping assistants, the industry will likely see further reductions in labour costs and improvements in inventory management. Regulatory frameworks around data privacy and AI transparency will shape the pace of adoption, while consumer acceptance of AI\u2011driven recommendations will determine the long\u2011term success of these technologies. Industry observers anticipate that by 2027, a majority of urban retail outlets in the region will have implemented at least one AI\u2011driven operational function, marking a significant milestone in the digital transformation of the APAC retail sector.<\/p>\n","protected":false},"excerpt":{"rendered":"
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