Artificial intelligence (AI) is rapidly penetrating the grocery retail space, moving from analytics and pilots into workflows and day-to-day execution. The trend is strong across Asia-Pacific (APAC), due to dense urban stores, high labor churn, and competitive quick-commerce ecosystems. A 2025 Q4 survey corroborates this, in which 45% of consumers in Asia and Australasia responded that they were very or quite likely to purchase a product based on recommendations or endorsements by AI, according to GlobalData, a leading intelligence and productivity platform.
Jaya Dandey, Consumer Analyst at GlobalData, comments: “Whether shoppers realize it or not, machine-learning systems have long been deciding when to encourage consumers to make purchases, which products they can see, and what discounts they can avail. Now, agentic systems can also complete shopping-related tasks end-to-end.”
Lawson was the first Japanese convenience store retailer to introduce AI-enabled “Lawson Go” stores in 2022. The brand collaborated with technology provider CloudPick in 2025 to integrate the latest AI, machine learning, and computer vision to enhance customer experience by eliminating check-out lines and the need for cashiers. In 2024, South Korean retail AI company Fainders.AI introduced a compact and cashier-less MicroStore in a gym, enhancing the accessibility of autonomous retail across various businesses.
AI is especially useful in forecasting and automation of replenishment, particularly in APAC, where store footprints can be small and replenishment frequency is high. The Japanese food retail chain Coop Sapporo uses Soracom’s camera-based AI system (Sora-cam) to avoid overstocking and reduce unsold merchandise on store shelves. It employs an analytics team to analyze the images generated to determine and arrive at the best shelf display ratio. The system also alerts staff to apply discount labels on close-to-expiry food items to prevent wastage.
Alongside monitoring waste and markdown timing, AI models can improve the efficiency of promotions. In Southeast Asian (SEA) markets with high price sensitivity, even small improvements in promotion efficiency can significantly improve profit margins. AI-driven labor optimization measures, such as scheduling, task priority lists, and workload balancing, are useful in Japan/South Korea where labor shortages are structural, as well as in high-growth SEA markets, where efficiency is key.
Dandey adds: “While the above technologies enhance operations, agentic AI can enhance the consumer experience. In food retail, agentic AI is best understood as an AI “operator” that can understand a goal, plan steps, stay within budget or allergen constraints, execute actions across systems, ask clarifying questions, and learn preferences over time.”
Instead of searching item-by-item, customers can express overall intent, for instance, by narrowing it down to “Plan five dinners for a family of four, mostly Asian recipes, no shellfish, under 45 minutes”. The agent generates recipes, builds a shopping cart, sizes quantities, and adds staples to the cart if missing. This is crucial for the region, as most APAC households cook frequently and shop fresh. Recipe- and cuisine-aware AI agents fit local habits (Korean banchan, Japanese bentos, Indian spice bases) better than generic Western meal plans.
Dandey concludes:“In many APAC markets, shopping is already deeply integrated with digital wallets, messaging apps, ride-hailing, and delivery ecosystems, making it easier for agentic AI to plug into daily routines. Nevertheless, some key challenges need to be overcome; ensuring private data sharing consent, minimizing hallucinations in terms of allergens and ingredients, and implementing proper localization of the system with language nuance.”
