IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2604.21672.html

Agentic Artificial Intelligence in Finance: A Comprehensive Survey

Author

Listed:
  • Irene Aldridge
  • Jolie An
  • Riley Burke
  • Michael Cao
  • Chia-Yi Chien
  • Kexin Deng
  • Ruipeng Deng
  • Yichen Gao
  • Olivia Guo
  • Shunran He
  • Zheng Li
  • George Lin
  • Weihang Lin
  • Percy Lyu
  • Alex Ng
  • Qi Wang
  • Hanxi Xiao
  • Dora Xu
  • Yuanyuan Xue
  • Sheng Zhang
  • Sirui Zhang
  • Yun Zhang
  • Sirui Zhao
  • Xiaolong Zhao
  • Yihan Zhao
  • Waner Zheng

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.

Suggested Citation

  • Irene Aldridge & Jolie An & Riley Burke & Michael Cao & Chia-Yi Chien & Kexin Deng & Ruipeng Deng & Yichen Gao & Olivia Guo & Shunran He & Zheng Li & George Lin & Weihang Lin & Percy Lyu & Alex Ng & Q, 2026. "Agentic Artificial Intelligence in Finance: A Comprehensive Survey," Papers 2604.21672, arXiv.org.
    • Handle: RePEc:arx:papers:2604.21672
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2604.21672
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2604.21672. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.