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

2026-05-07

AI Summary

This work addresses the challenge that large language models struggle to transform fragmented data into actionable insights in complex enterprise environments—characterized by intricate database schemas, difficulties in dynamic SQL generation, and insufficient multidimensional deep analysis. To overcome these limitations, we propose AIDA, an end-to-end autonomous insight discovery agent. AIDA uniquely integrates a domain-specific language (DSL) with reinforcement learning to align semantic reasoning with precise SQL execution and employs the Pareto principle to guide cumulative, multidimensional exploration. Evaluated in an instant retail setting encompassing over 200 metrics and 100 dimensions, AIDA significantly outperforms workflow-based agents, demonstrating superior capabilities in environmental awareness and multi-perspective deep analysis, thereby validating the transformative potential of autonomous intelligence in industrial-scale business intelligence.

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.

Problem

• Business Intelligence
• Data-to-Insight
• Autonomous Agent
• Multi-dimensional Analysis
• Enterprise Data

Innovation

• Autonomous Business Intelligence
• Domain-Specific Language (DSL)
• Reinforcement Learning
• Pareto Principle-guided Reasoning
• End-to-End Insight Discovery