A study of the core areas of AI-driven online services is offered in this present study in the banking sector, with a stronger focus on elevating customer satisfaction. The integration of advanced AI technologies across various banking services—such as smart ATMs, online banking, and net banking—has transformed the customer experience. Smart ATMs use AI to provide specialized services and enhanced security, giving rise to ease of transactions for customers. The real-time financial insights, personalized financial advice, and efficient transaction processing from AI-based online banking are shown to elevate customer satisfaction. Net banking employs machine learning algorithms to analyse spending patterns and financial behaviours for fraud detection and customer experience enhancement. This research also utilized Cronbach's Alpha, regression analysis, and descriptive statistics to evaluate the performance of AI-driven technologies in the banking industry. The results demonstrated increased efficiency across all parameters, ultimately leading to improved customer satisfaction. Through machine learning and data analytics, banks can improve their credit assessments across different variables involving financial history, spending habits, and social behaviour’s. These parameters allow for quicker and highly accurate credit assessments compared to traditional methods, greatly shortening loan approval times and enabling customers to access funds almost instantly. AI is also aiding in personalized lending, whereby financial products are tailored to fit individual needs, consequently improving customer satisfaction levels. Another area where AI is protecting the industry is in fraud detection; it serves to identify simulations of incidents or suspicious trends or patterns, curating an environment for safe lending. In summation, the paper presents how AI in banking is supporting inclusivity, transparency, and better operational efficiency for the benefit of lenders, borrowers, and customer experience at large.