Artificial Intelligence (AI) tools, such as robo-advisors, predictive analytics, and risk management systems, are transforming investment decision-making in India's rapidly expanding financial markets. With over 120 million retail investors participating in the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE), AI-driven platforms play a critical role in enhancing decision accuracy, mitigating behavioral biases, and improving market efficiency. This systematic literature review follows PRISMA guidelines, synthesizes 16 selected sources, primarily peer-reviewed articles and authoritative reports published between 2020 and 2026. The review evaluates AI applications, empirical performance outcomes—including predictive accuracy improvements of 20–30% in several emerging-market studies, high investor acceptance (mean scores around 4.2 approximately on five-point Likert scales from TAM-based surveys), and notable enhancements in risk management and fraud detection through AI tools—and persistent challenges related to regulation and data privacy under the Digital Personal Data Protection (DPDP) Act, 2023. Thematic analysis following Braun and Clarke (2006) identifies three dominant clusters: LSTM-based Nifty forecasting models, robo-advisory platforms integrated with UPI systems, and real-time AI-driven risk management frameworks contributing to improved operational efficiency and market surveillance. The findings highlight India's rapid FinTech adoption relative to global trends while emphasizing concerns related to algorithmic opacity. The study extends the Technology Acceptance Model (TAM) by incorporating data privacy as a moderating factor and advocates hybrid human–AI decision frameworks. Policy, educational, and research recommendations are proposed to support sustainable and explainable AI adoption in Indian capital markets.
Kozhithodi et al. (Thu,) studied this question.