LLM-Driven Business Intelligence for Retail Digital Transformation: A Decision Support System Case Study — Wang & Zhang (2026)
The rapid digital transformation of the retail industry has generated increasing demand for intelligent business intelligence systems that can translate natural language managerial inquiries into actionable analytical and predictive decisions. However, existing enterprise analytics solutions either rely on rigid dashboard-based querying or isolated AI models, and thus struggle to jointly achieve knowledge grounding, executable analytical reasoning, and decision-oriented synthesis within a unified framework. RIDE constructs knowledge-grounded analytical contexts from enterprise repositories…
The skinny
The skinny isn't ready yet — notes appear once the transcript is processed.