Lotte Department Store Uses Ontology-Based Brand AI to Support MD Decision-Making
AI TIMES ·
✦ AI Summary
According to AI TIMES, Lotte Innovate has built a "Brand AI" system that helps Lotte Department Store with brand operations and sourcing dec…
According to AI TIMES, Lotte Innovate has built a "Brand AI" system that helps Lotte Department Store with brand operations and sourcing decisions. Unveiled on September 1, the system's key feature is an ontology-based structure that connects about 4,000 brands with sales, customer, and purchasing data in a way that fits business contexts. Rather than listing individual metrics, it analyzes similarity between brands and related purchase flows in a relationship-centered way, enabling frontline teams to understand market position and connectivity more intuitively. Business staff took part in the initial design and mockup implementation, reflecting on-site requirements in the technical architecture, and the analysis results were visualized in a format that is easy to compare and interpret. Generative AI is configured to gather and organize relevant information before creating insights within a standardized framework, while sensitive information is handled so it is not directly exposed. By tying together data building, analysis, and service operations support in one package, the case underscores its effort to make the system take root in actual work.
Perspective
The significance of this case lies in the fact that AI has been embedded into the frontline decision-making framework rather than treated as a separate experimental tool. In particular, by emphasizing a relationship-centered data structure, it strengthened its role as a decision-support tool rather than a simple query-based analysis system, and the effort to improve usability through frontline participation shows that, in future retail AX, the standard for evaluation is shifting from the technology itself to how well it is actually used. The approach of designing security and operational foundations together suggests that, in similar projects, the ability to settle into day-to-day operations after adoption could emerge as a key competitive advantage.
This perspective is BizCrush's own commentary and is not part of the reporting by AI TIMES.
This article was produced with the help of an automated content generation algorithm.
Source: AI TIMES
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