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arXiv · 2605.07202

Towards Autonomous Business Intelligence via Data-to-Insight Discovery Agent

Dongming Wu·Junwen Li·Ming Lu·Gang Wang·Ting Chen
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Abstract

Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limitations in dynamic SQL generation, and the need for deep multi-dimensional analysis.In this paper, we propose AIDA(Autonomous Insight Discovery Agent), the first end-to-end framework designed for autonomous exploration in complex business environments. We establish a highly flexible instant retail environment encompassing 200+ metrics and 100+ dimensions, and integrates a proprietary Domain-Specific Language (DSL) that bridges semantic reasoning with precise SQL execution. Our reinforcement learning system subsequently formulates business analysis as a Pareto Principle-guided cumulative reasoning process. Experimental results demonstrate that AIDA significantly outperforms workflow-based agents, and extensive evaluations further reveal that AIDA achieves superior environmental perception and more in-depth analysis from diverse perspectives. Our work ultimately establishes the transformative potential of autonomous intelligence for industrial-scale business intelligence systems.

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Dongming Wu, Junwen Li, Ming Lu, Gang Wang, Ting Chen. 2026-05-08. Towards Autonomous Business Intelligence via Data-to-Insight Discovery Agent. https://arxiv.org/abs/2605.07202

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