ABSTRACT:
Financial assistants driven by artificial intelligence offer a continuously and readily available service that includes assistance on investment plans, understanding of spending trends, and even answers to questions about banking-related activities. The banking sector's adoption of AI-powered financial assistants is completely changing the way financial services are delivered by offering convenience, individualized offerings, and improved efficient performance. The use of AI-powered financial assistants for banking-related operations is the most recent technical advancement in the banking sector. The aim of the current study is to investigate how demographic variables, such as age, affect customers' adoption factors of AI-driven financial assistants, given that more and more consumers are leaning toward tech-based services. The study used an adapted questionnaire to gather primary data, which included the dependent variable Behavioural Intention to use AI-driven financial assistants and the six primary adoption factors of AI-driven financial assistants: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Trust, and Personal Innovativeness. The data was collected from Haryana's banking customers via a survey. The results were determined using ANOVA. The study's findings demonstrate that, depending on the respondents' ages, customers' adoption factors of Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Trust, and Personal Innovativeness vary significantly. Additionally, behavioral intention to use AIFA differentiates groups according to the customers' ages. The results of this study will help banks and other financial institutions better understand their customers.