Data Agents: Rethinking Data Systems in the AI Agent Era

Abstract

The database community is at a pivotal moment. Large Language Models (LLMs) and AI agents are rapidly changing how users interact with data systems. The traditional model—where human experts write SQL queries or navigate complex BI tools—is being disrupted by a new vision: data agents capable of understanding natural language, reasoning about data semantics, autonomously executing multi-step analytical workflows, and collaborating with humans to derive insights. This shift introduces fundamental questions that span database systems, human-computer interaction, AI/ML infrastructure, and programming languages. This panel will convene leading researchers and practitioners to discuss the future of data agents. A "data agent" is defined as an autonomous system capable of perceiving data in various forms (structured, semi-structured, and unstructured), planning and executing complex data manipulation and analysis tasks, interacting with humans through natural language or other intuitive interfaces, and learning from feedback to improve over time. The panel will examine whether this vision is achievable, the technical obstacles that need to be addressed, and how the database community should adapt to meet this emerging challenge.