A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
The rapid advancement of large language models (LLMs) has spurred the
emergence of data agents--autonomous systems designed to orchestrate Data + AI
ecosystems for tackling complex data-related tasks. However, the term "data
agent" currently suffers from terminological ambiguity and inconsistent
adoption, conflating simple query responders with sophisticated autonomous
architectures. This terminological ambiguity fosters mismatched user
expectations, accountability challenges, and barriers to industry growth.
Inspired by the SAE J3016 standard for driving automation, this survey
introduces the first systematic hierarchical taxonomy for data agents,
comprising six levels that delineate and trace progressive shifts in autonomy,
from manual operations (L0) to a vision of generative, fully autonomous data
agents (L5), thereby clarifying capability boundaries and responsibility
allocation. Through this lens, we offer a structured review of existing
research arranged by increasing autonomy, encompassing specialized data agents
for data management, preparation, and analysis, alongside emerging efforts
toward versatile, comprehensive systems with enhanced autonomy. We further
analyze critical evolutionary leaps and technical gaps for advancing data
agents, especially the ongoing L2-to-L3 transition, where data agents evolve
from procedural execution to autonomous orchestration. Finally, we conclude
with a forward-looking roadmap, envisioning the advent of proactive, generative
data agents.
690065ad22d452aac6dd4454
Yizhang Zhu
690065ad22d452aac6dd4455
Liangwei Wang
690065ad22d452aac6dd4456
Chenyu Yang
690065ad22d452aac6dd4457
Xiaotian Lin
690065ad22d452aac6dd4458
Boyan Li
690065ad22d452aac6dd4459
Wei Zhou
690065ad22d452aac6dd445a
Xinyu Liu
690065ad22d452aac6dd445b
Zhangyang Peng
690065ad22d452aac6dd445c
Tianqi Luo
690065ad22d452aac6dd445d
Yu Li
690065ad22d452aac6dd445e
Chengliang Chai
690065ad22d452aac6dd445f
Chong Chen
690065ad22d452aac6dd4460
Shimin Di
690065ad22d452aac6dd4461
Ju Fan
690065ad22d452aac6dd4462
Ji Sun
690065ad22d452aac6dd4463
Nan Tang
690065ad22d452aac6dd4464
Fugee Tsung
690065ad22d452aac6dd4465
Jiannan Wang
690065ad22d452aac6dd4466
Chenglin Wu
690065ad22d452aac6dd4467
Yanwei Xu
690065ad22d452aac6dd4468
Shaolei Zhang
690065ad22d452aac6dd4469
Yong Zhang
690065ad22d452aac6dd446a
Xuanhe Zhou
claimed_verified
2026-02-27T16:47:17.908Z
64ef522242da8d2a897d62da
/avatars/03611010d247da66696ac8976d4d3ed3.svg
xuanhe zhou
zhouxh19
user
zhouxh19
690065ad22d452aac6dd446b
Guoliang Li
690065ad22d452aac6dd446c
Yuyu Luo
A Survey of Data Agents: Emerging Paradigm or Overstated Hype?
The rapid advancement of large language models (LLMs) has spurred the
emergence of data agents--autonomous systems designed to orchestrate Data + AI
ecosystems for tackling complex data-related tasks. However, the term "data
agent" currently suffers from terminological ambiguity and inconsistent
adoption, conflating simple query responders with sophisticated autonomous
architectures. This terminological ambiguity fosters mismatched user
expectations, accountability challenges, and barriers to industry growth.
Inspired by the SAE J3016 standard for driving automation, this survey
introduces the first systematic hierarchical taxonomy for data agents,
comprising six levels that delineate and trace progressive shifts in autonomy,
from manual operations (L0) to a vision of generative, fully autonomous data
agents (L5), thereby clarifying capability boundaries and responsibility
allocation. Through this lens, we offer a structured review of existing
research arranged by increasing autonomy, encompassing specialized data agents
for data management, preparation, and analysis, alongside emerging efforts
toward versatile, comprehensive systems with enhanced autonomy. We further
analyze critical evolutionary leaps and technical gaps for advancing data
agents, especially the ongoing L2-to-L3 transition, where data agents evolve
from procedural execution to autonomous orchestration. Finally, we conclude
with a forward-looking roadmap, envisioning the advent of proactive, generative
data agents.
A systematic taxonomy for data agents is introduced to clarify their autonomy levels and capabilities, addressing terminological ambiguity and guiding future research and development.
large language models data agents SAE J3016 standard driving automation hierarchical taxonomy autonomy levels data management data preparation data analysis generative data agents