Harnessing the Power of AI: Transformations in the APAC Retail Sector
AI technology in the APAC retail sector is evolving, moving from mere analytics and pilot programs into full-scale workflows and daily operations. This shift is driven by factors such as dense urban populations, high employee turnover, and the need for rapid service in competitive quick-commerce markets.
According to a survey by GlobalData conducted in Q4 2025, 45% of consumers in Asia and Australasia are likely to purchase products influenced by AI suggestions or endorsements. Jaya Dandey, a Consumer Analyst at GlobalData, emphasizes that machine learning systems have been subtly steering consumer decisions—determining visibility of products, discount offerings, and even completion of shopping-related tasks.
Automation and Computer Vision Implementation
Retailers exploring computer vision and machine learning capabilities are already seeing significant applications. For instance, Lawson launched AI-enabled ‘Lawson Go’ stores in Japan in 2022, later partnering with CloudPick to integrate AI for a seamless shopping experience that removes the need for checkout lines.
In South Korea, Fainders.AI introduced a cashier-less MicroStore within a gym in 2024, enhancing the accessibility of autonomous retail formats. AI is also significantly affecting supply chain processes, aiding in efficient replenishment suited for small store formats frequently seen in the APAC market.
A notable example includes Coop Sapporo, a food retail chain in Japan, utilizing a camera-based AI system called Sora-cam to reduce overstock and manage inventory effectively. This system analyzes images to optimize shelf display ratios while alerting staff to apply discounts on near-expiry products, thus minimizing waste.
Moreover, AI is leveraged for labor optimization—helping with scheduling, prioritizing tasks, and balancing workloads—crucial for retailers in Japan and South Korea experiencing labor shortages and operational inefficiencies.
Enhanced Consumer Interaction through Agentic AI
Dandey describes agentic AI in food retail as an AI “operator” capable of understanding objectives, planning necessary steps, executing actions, and learning user preferences. Customers can now engage in more intuitive shopping experiences, such as requesting meal plans tailored to their dietary restrictions, which the AI can generate and automate into a shopping cart.
In the context of regional habits, where many households frequently prepare home-cooked meals, AI agents that can recognize and cater to local cuisines are much more relatable than generic Western meal planning tools.
The integration of shopping with digital payment systems, messaging platforms, and various delivery services in many APAC markets makes it easier for agentic AI applications to fit into everyday routines. However, challenges remain that need addressing, such as ensuring consumer consent for data sharing, reducing inaccuracies regarding allergens, and providing localization to capture linguistic subtleties.
For those interested in the intersection of AI and big data in retail, more information can be found at the AI & Big Data Expo.
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