Analyzing Customer Adoption of AI-Based Chatbots in Retail Banking Using a Hybrid Structural Equation Modeling Approach

The usage of AI in the banking industry has totally transformed how consumers are addressed. This is due of chatbots that use AI. These technologies can help retail banks decrease expenses, improve the customer experience, and offer service around the clock. There are still a lot of elements that determine how much individuals are willing to talk to chatbots powered by AI, like the technology, the situation, and their own behavior. This study looks at the major reasons why people use AI chatbots in retail banking. Three hundred and fifty retail banking customers filled out a standardized questionnaire to give information. We used structural equation modeling (SEM) and machine learning to find links and guess how users would use the product. The survey concluded that customers are more likely to employ chatbots if they think they are useful, easy to use, trustworthy, and responsive. Trust is also what connects chatbot response and adoption, which are two things that depend on each other. The model could make predictions with 89% accuracy using Random Forest classification. These results give banks and other financial institutions good ideas for how to improve chatbots and use them more.