From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery

Jiaqi Wei; Yuejin Yang; Xiang Zhang; Yuhan Chen; Xiang Zhuang; Zhangyang Gao; Dongzhan Zhou; Guangshuai Wang; Zhiqiang Gao; Juntai Cao; Zijie Qiu; Ming Hu; Chenglong Ma; Shixiang Tang; Junjun He; Chunfeng Song; Xuming He; Qiang Zhang; Chenyu You; Shuangjia Zheng; Ning Ding; Wanli Ouyang; Nanqing Dong; Yu Cheng; Siqi Sun; Lei Bai; Bowen Zhou

arXiv · 2508.14111

From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery

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Abstract

Artificial intelligence (AI) is reshaping scientific discovery, evolving from specialized computational tools into autonomous research partners. We position Agentic Science as a pivotal stage within the broader AI for Science paradigm, where AI systems progress from partial assistance to full scientific agency. Enabled by large language models (LLMs), multimodal systems, and integrated research platforms, agentic AI shows capabilities in hypothesis generation, experimental design, execution, analysis, and iterative refinement -- behaviors once regarded as uniquely human. This survey provides a domain-oriented review of autonomous scientific discovery across life sciences, chemistry, materials science, and physics. We unify three previously fragmented perspectives -- process-oriented, autonomy-oriented, and mechanism-oriented -- through a comprehensive framework that connects foundational capabilities, core processes, and domain-specific realizations. Building on this framework, we (i) trace the evolution of AI for Science, (ii) identify five core capabilities underpinning scientific agency, (iii) model discovery as a dynamic four-stage workflow, (iv) review applications across the above domains, and (v) synthesize key challenges and future opportunities. This work establishes a domain-oriented synthesis of autonomous scientific discovery and positions Agentic Science as a structured paradigm for advancing AI-driven research.

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Jiaqi Wei, Yuejin Yang, Xiang Zhang, Yuhan Chen, Xiang Zhuang, Zhangyang Gao, Dongzhan Zhou, Guangshuai Wang, Zhiqiang Gao, Juntai Cao, Zijie Qiu, Ming Hu, Chenglong Ma, Shixiang Tang, Junjun He, Chunfeng Song, Xuming He, Qiang Zhang, Chenyu You, Shuangjia Zheng, Ning Ding, Wanli Ouyang, Nanqing Dong, Yu Cheng, Siqi Sun, Lei Bai, Bowen Zhou. 2025-10-20. From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discovery. https://arxiv.org/abs/2508.14111

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