To Study the Impact of Adoption and Trust in AI-Based Robo-Advisory Platforms Among Investors in Raipur

This research investigates the factors influencing the adoption of AI-based robo-advisory platforms among retail investors in Raipur, Chhattisgarh. As financial services transition toward automation, understanding how individual investors in emerging markets perceive non-human financial advice is critical. While most studies focus on Tier-1 metropolitan areas, this research addresses a significant geographical gap by providing localized insights into a Tier-2 commercial hub. Using a quantitative descriptive design, primary data was collected from 75 active investors through purposive sampling. The study utilizes the Technology Acceptance Model (TAM) to analyse how variables such as trust, perceived risk, and perceived ease of use affect an investor’s willingness to use AI platforms. Furthermore, it bridges a behavioural gap by measuring actual capital allocation—the percentage of wealth investors are willing to entrust to algorithms. Data was analysed using Microsoft Excel, employing manual calculations for Pearson Correlation and Independent t-tests to verify hypotheses. The findings aim to assist fintech developers and financial institutions in building trust and increasing digital adoption within localized Indian markets. The study concludes that addressing the