The retail landscape in the Asia-Pacific (APAC) region is experiencing a profound transformation as artificial intelligence transitions from analytical tools and limited trials into fundamental daily operations. This accelerated adoption is fueled by several factors, including dense urban populations, significant employee turnover, and highly competitive quick-commerce ecosystems. A Q4 2025 survey by GlobalData highlighted growing consumer trust, indicating that 45 percent of shoppers in Asia and Australasia are quite or very likely to make a purchase based on AI-generated recommendations or endorsements.
Jaya Dandey, a Consumer Analyst at GlobalData, noted that machine-learning systems have long played a subtle role in influencing consumer buying decisions, dictating product visibility and available discounts. However, she emphasized that today's advanced agentic systems are now capable of managing entire shopping-related tasks from start to finish.
Smart Automation and Computer Vision in Stores
Retail enterprises across APAC are actively exploring and implementing early versions of computer vision and machine learning technologies. A notable example is Lawson, which introduced AI-powered 'Lawson Go' stores in Japan during 2022. By 2025, the retailer collaborated with technology provider CloudPick to integrate AI, machine learning, and computer vision, effectively eliminating traditional checkout lines and cashiers to significantly enhance the customer journey.
In South Korea, retail AI firm Fainders.AI launched a compact, cashier-less MicroStore within a gym in 2024. This innovative deployment showcased the broader applicability of autonomous retail solutions across diverse business environments. Beyond the front end, AI also proves invaluable in forecasting and automating retail replenishment—a particularly beneficial capability for the APAC market, characterized by smaller store footprints and a high frequency of inventory turnover.
Japanese food retailer Coop Sapporo leverages a camera-based AI system called Sora-cam, developed by Soracom. This system helps the chain prevent overstocking and reduce unsold items on shelves. An analytics team evaluates the images captured, determining optimal shelf display ratios. The Sora-cam system further alerts staff to apply discount labels to food items nearing their expiry date, significantly minimizing waste.
Such AI models are instrumental in tracking waste and optimizing markdown timing, while simultaneously boosting the effectiveness of promotions. In Southeast Asian markets, where price sensitivity is often high, even marginal improvements in promotion efficiency can translate into substantial increases in profit margins.
AI-Driven Labour Optimization
AI also contributes significantly to labour optimization through features like automated scheduling, prioritized task lists, and balanced workload distribution. These measures are particularly beneficial for retailers in Japan and South Korea, which contend with structural labour shortages. Additionally, they provide considerable efficiency gains in the high-growth markets of Southeast Asia.
Agentic AI Enhances APAC Consumer Interaction
According to Dandey, agentic AI in food retail can be conceptualized as an AI 'operator' that can comprehend a specific objective, devise a plan, adhere to budget or allergen constraints, execute actions across multiple systems, seek clarification, and progressively learn consumer preferences over time. This new paradigm allows customers to articulate their overall intent rather than searching for individual items. For example, a customer might instruct an AI agent to 'Plan five dinners for a family of four, mostly Asian recipes, no shellfish, under 45 minutes.' The agent would then generate suitable recipes, assemble a shopping cart, adjust quantities, and add any essential missing pantry items.
This agentic AI capability aligns well with prevalent regional behaviours, as many APAC households frequently cook at home and prioritize fresh produce. AI agents that recognize and incorporate local culinary traditions—such as Korean banchan, Japanese bentos, or various Indian spice bases—offer a more tailored and relevant experience compared to generic Western meal plans. Dandey further explained that in many APAC markets, shopping is already seamlessly integrated with digital wallets, messaging applications, ride-hailing services, and delivery platforms, making it easier for agentic AI to embed itself into daily routines.
However, several critical challenges must be addressed for widespread adoption. These include ensuring explicit consent for private data sharing, minimizing 'hallucinations' regarding allergens and ingredients, and implementing precise localization of the system to accommodate language nuances and cultural specifics.
This article is a rewritten summary based on publicly available reporting. For the original story, visit the source.
Source: AI News
