Naver enhances its shopping AI agent to deliver proactive, personalised recommendations, reflecting a broader industry shift towards AI-driven commerce and anticipatory shopping experiences.
NAVER has pushed its shopping AI agent beyond passive assistance, moving it towards proactive conversation inside the NAVER Plus Store app. According to NAVER’s February launch note, the beta service was designed to summarise product information, analyse reviews and give tailored shopping guidance from user-entered keywords. In practice, that meant a search such as “sofa” could trigger brand suggestions and buying tips rather than a simple list of results.
The company said in June that the agent was updated to start conversations with users instead of waiting for prompts. That change allows it to recommend items linked to previously saved products and to respond to shopping context, making the experience more personal and more active. NAVER has framed the work as part of a wider plan to turn its services into an “agent platform”, embedding AI across its portfolio so that systems can understand intent and carry out tasks.
The latest update, reported by Newsis in August, takes that logic further by having the agent suggest products before a user asks. For example, if someone repeatedly browses meal kits, the system may recommend single-serving options aimed at one-person households. The result is a shopping assistant that tries to anticipate demand, not merely interpret it.
The broader market is moving in the same direction. Newsis noted that Kakao is developing “Kanana A2A” to understand conversation context and connect chat, ordering and payment in one flow. It also pointed to Walmart’s Sparky, which the company says lifted average order value by 35%, as evidence that AI-guided commerce is already affecting sales metrics. By 2030, Walmart expects AI to handle a quarter of its e-commerce execution, underscoring how quickly shopping assistants are becoming commercial infrastructure rather than experimental features.
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