Convergence of Robo-Advisors and Artificial Intelligence in FinTech: Insights, Challenges, and Innovations in the Indian Financial Services Market

Abstract

Introduction: The integration of artificial intelligence (AI) into robo-advisory services is reshaping India’s financial sector, yet adoption faces challenges such as low trust, transparency gaps, and data security concerns. These barriers hinder the potential of AI-driven platforms to democratize investment opportunities in a rapidly growing market.

Objectives: This study examines how AI can enhance trust, transparency, and personalization in Indian robo-advisory services, while addressing generational disparities in adoption and aligning platforms with investor preferences in financial planning and portfolio diversification.

Methods: A mixed-methods approach was employed, combining secondary data analysis of global and Indian market trends with primary research via a structured questionnaire survey of 163 Indian investors. Regression analysis and path modelling were used to evaluate key drivers of adoption.

Results: Younger investors (20–40 years) showed higher receptiveness to AI-driven platforms, while older demographics remained cautious due to privacy concerns. Trust, though critical, had the weakest influence (β = 0.22), whereas ease of use (β = 0.34) and perceived benefits (β = 0.28) emerged as stronger predictors of adoption. Domestic platforms lagged behind international counterparts in user trust, with only 29.2% of assets managed locally.

Conclusions: To unlock growth, Indian robo-advisors must prioritize transparency, user-centric design, and hyper-localized solutions. Bridging trust gaps through regulatory frameworks and hybrid human-AI models could catalyse adoption in India’s tech-savvy yet diverse investor landscape.