Business Utility of Large Language Models as Exploratory Data Analysis Agents
Large Language Models (LLMs) are increasingly used in analytical workflows, but their suitability as exploratory data analysis (EDA) agents in business settings remains uncertain. In practice, a deployable EDA agent must provide not only useful average performance but also sufficient repeatability to support trust in its outputs. We evaluate this requirement in a controlled, business-relevant benchmark built on an agent-based supply chain simulation. The task is to identify supplier-product combinations responsible for low quality and downstream sales loss by reasoning from indirect operational traces rather than from explicit labels. Fifteen model-variant configurations from eight model ...
| Authors | Rafał Łabędzki, Patryk Miziuła, Hubert Rutkowski et al. |
|---|---|
| Primary category | cs.CY |
| Published | 8 May 2026 |
| Last updated at source | 8 May 2026 |
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