Artificial Intelligence Integration in Indonesian Capital Markets: A Literature Review of Robo-Advisor Adoption, Behavioral Biases, and Regulatory Gaps Among Accounting Student-Investors

Abstract

This study presents a structured literature review of 30 peer-reviewed studies published between 2015 and 2025, examining how AI-powered platforms, specifically robo-advisors such as Ajaib, Bibit, and Stockbit, influence investment decision-making among accounting students as retail investors. It also investigates whether robo-advisors moderate behavioral biases in this population and whether the OJK regulatory framework adequately governs the risks arising from algorithmic opacity. The review synthesizes evidence from Google Scholar, Scopus, Web of Science, SSRN, and the Garuda portal, selected through a systematic search and screening process.The findings reveal a central paradox. Despite possessing accounting literacy, student-investors continue to exhibit significant behavioral biases. Robo-advisors have the potential to moderate these biases, but only when users possess sufficient AI literacy. In terms of regulation, OJK Regulation (POJK) No. 22 of 2023, hereinafter referred to as POJK 22/2023, establishes obligations related to suitability assessments, transparency, and the fair treatment of financial consumers. However, it does not yet contain specific provisions addressing AI-mediated risks in the capital market.The novelty of this study lies in three main contributions. First, it focuses exclusively on accounting students as a distinct investor group whose domain knowledge has not fully eliminated behavioral biases. Second, it integrates behavioral accounting and AI governance literature within a single analytical framework. Third, it evaluates robo-advisors as behavioral scaffolds within Indonesia’s regulatory environment, a combination that has not been examined in previous review studies.