IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2604.19833.html

From Clerks to Agentic-AI: How will Technology Change Labor Market in Finance?

Author

Listed:
  • Lu Yu
  • Xiang Li

Abstract

Financial firms have gone through three major technological waves: computerization in the 1980s and 1990s, the rise of indexing and passive investing in the 2000s and 2010s, and the AI and automation wave from roughly 2015 to the present. This project studies how much labor is required to manage capital across those waves by tracking a simple productivity measure: assets under management per employee. Using a small panel of representative firms, we compare changes in AUM per employee, revenue per employee, and operating expense intensity over time. The goal is not to identify causal effects, but to document stylized facts about how technology changes the scale of asset management work.

Suggested Citation

  • Lu Yu & Xiang Li, 2026. "From Clerks to Agentic-AI: How will Technology Change Labor Market in Finance?," Papers 2604.19833, arXiv.org.
    • Handle: RePEc:arx:papers:2604.19833
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2604.19833
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Erik Brynjolfsson & Anton Korinek & Ajay K. Agrawal, 2025. "A Research Agenda for the Economics of Transformative AI," NBER Working Papers 34256, National Bureau of Economic Research, Inc.
    2. Ajay K. Agrawal & Erik Brynjolfsson & Anton Korinek, 2025. "Introduction to "The Economics of Transformative AI"," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.
    3. Daron Acemoglu & Jonas Loebbing, 2026. "Automation and Polarization," Journal of Political Economy, University of Chicago Press, vol. 134(3), pages 1017-1072.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alexander Eliseev & Sergei Seleznev, 2026. "Fake Date Tests: Can We Trust In-sample Accuracy of LLMs in Macroeconomic Forecasting?," Papers 2601.07992, arXiv.org, revised Mar 2026.
    2. Liu, Yan & Wang, He & Yu, Shu, 2025. "Labor Demand in the Age of Generative AI : Early Evidence from the U.S. Job Posting Data," Policy Research Working Paper Series 11263, The World Bank.
    3. Dumont, Michel & Rayp, Glenn, 2025. "Belgian start-ups in Artificial Intelligence," MPRA Paper 126994, University Library of Munich, Germany.
    4. Scott Counts & Yan Chen & Jing Dong & Himanshu Sharma & Andrey Zaikin & Rui Hu & Alperen Kok & Gorkem Ozer Yilmaz & Siddharth Suri & Kiran Tomlinson & Sonia Jaffe & Will Wang, 2026. "AI in the Enterprise: How People Use M365 Copilot Chat," Papers 2605.23958, arXiv.org.
    5. Christian Catalini & Xiang Hui & Jane Wu, 2026. "Some Simple Economics of AGI," Papers 2602.20946, arXiv.org, revised Feb 2026.
    6. Anton Korinek & Lee M. Lockwood, 2026. "Public Finance in the Age of AI: A Primer," NBER Chapters, in: The Economics of Transformative AI, National Bureau of Economic Research, Inc.

    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:2604.19833. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: https://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.