Agentic Artificial Intelligence in Finance: A Comprehensive Survey

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Authors: Irene Aldridge, Jolie An, Riley Burke, Michael K. Cao, Chia-Yi Chien, Kexin Deng, Rui Deng, Yichen Gao, Olivia Guo, Shunran He, Zheng Li, George Lin
+14 more Weihang Lin, Fanyi Lyu, K J Ng, Qi Wang, Hanxi Xiao, Dora Xu, Yuanyuan Xue, Sheng Zhang, Sirui Zhang, Yun Zhang, Sirui Zhao, Xiaolong Zhao, Yihan Zhao, Waner Zheng
Cited by: 2
References: 5

Abstract

The emergence of agentic artificial intelligence (AI) represents a fundamental transformation in financial markets, characterized by autonomous systems capable of reasoning, planning, and adaptive decision-making with minimal human intervention. This comprehensive survey synthesizes recent advances in agentic AI across multiple dimensions of financial operations, including system architecture, market applications, regulatory frameworks, and systemic implications. We examine how agentic AI differs from traditional algorithmic trading and generative AI through its capacity for goal-oriented autonomy, continuous learning, and multi-agent coordination. Our analysis shows that while agentic AI offers substantial potential for enhanced market efficiency, liquidity provision, and risk management, it also introduces novel challenges related to market stability, regulatory compliance, interpretability, and systemic risk. Through a systematic review of foundational research, technical architectures, market applications, and governance frameworks, this survey provides scholars and practitioners with a structured understanding of how agentic AI is reshaping financial markets and identifies critical research directions for ensuring that these systems enhance both operational efficiency and market resilience.

Fields of Study & Subjects

Stock Market Forecasting Methods Complex Systems and Time Series Analysis Financial Markets and Investment Strategies

Publication details

Journal / source
SSRN Electronic Journal
Publisher
Elsevier BV
Publication date
1 January 2026
Document type
Preprint