Artificial Intelligence in Finance : The Journey of Robo Advisors So Far and the Way Ahead

Authors

  •   Rishabh Jain Assistant Professor, Sparsh Global Business School, Plot No. 29/2, Knowledge Park III, Greater Noida - 210 310, Uttar Pradesh ORCID logo https://orcid.org/0000-0001-7212-2830
  •   Abhinav Pal Assistant Professor, Symbiosis Centre for Management Studies, Plot No. 47 & 48, Symbiosis International (Deemed University), Noida, Sector 62, Noida - 201 301, Uttar Pradesh ORCID logo https://orcid.org/0000-0002-8045-0102
  •   Kanishka Gupta Assistant Professor, Vivekananda School of Business Studies, Vivekananda Institute of Professional Studies – Technical Campus, Outer Ring Rd, AU Block, Ranikhet, Pitampura, New Delhi, Delhi - 110 034 ORCID logo https://orcid.org/0000-0001-7211-7652
  •   Dolly Gaur Assistant Professor (Corresponding Author), Institute of Business Management, GLA University, Mathura - 281 406, Uttar Pradesh ORCID logo https://orcid.org/0000-0002-3868-5397

DOI:

https://doi.org/10.17010/ijf/2026/v20i1/174132

Keywords:

robo-advisory, artificial intelligence, fintech, asset allocation, portfolio management.
JEL Classification Codes : C33, E580, G210
Publication Chronology: Paper Submission Date : January 5, 2025 ; Paper sent back for Revision : May 13, 2025 ; Paper Acceptance Date : August 25, 2025 ; Paper Published Online : January 15, 2026

Abstract

Purpose : This bibliometric research article aimed to provide a comprehensive overview of the academic literature on robo-advisory services in finance, identifying key trends, influential factors, and potential avenues for future research.

Design/Methodology/Approach : A systematic bibliometric analysis was conducted for scholarly articles published on the topic of robo-advisory between 2016 and 2022. The metadata was sourced from two premier research databases : SCOPUS and Web of Science. The metadata of 210 documents was analyzed using the Bibliometrix package of R.

Results : A substantial growth in research on robo-advisory services in finance over the past decade was found. The application of robo-advisory in terms of asset allocation and portfolio optimization was seen. While most of the research focused on the technology enablers of robo-advisory, the applications offer further areas of study.

Practical Implications : The findings suggested promising avenues for future research, including the further integration of artificial intelligence and machine learning techniques in financial decision-making.

Originality : The study attempted to touch upon different aspects of this topic in terms of its enablers, technology, applications, and challenges faced. This research tried to design a path for further work in this field by suggesting a few bases that have not been studied much yet.

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Published

2026-01-15

How to Cite

Jain, R., Pal, A., Gupta, K., & Gaur, D. (2026). Artificial Intelligence in Finance : The Journey of Robo Advisors So Far and the Way Ahead. Indian Journal of Finance, 20(1), 47–71. https://doi.org/10.17010/ijf/2026/v20i1/174132

Issue

Volume 20, Issue 1, January 2026

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

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