Study of AI-enabled chatbots driving customer experience and intention to recommend

This study examines the impact of conversational AI banking chatbots on enhancing Online Customer Experience (OCE) and influencing customers' intention to recommend (ITR) banking services. A sample of 459 digital banking users, predominantly professionals from the banking sector, was collected via convenience sampling. Using structural equation modelling, the study found that Perceived Anthropomorphism (PAN), personalisation (PER), and perceived control (PCO) positively influenced OCE, while Perceived Risk (PRI) had a negative effect. The strongest predictor of ITR was OCE, with a significant path coefficient of 0.796. AI chatbots employed Natural Language Processing (NLP) and machine learning models, optimised for banking interactions. Despite their effectiveness, the preference for human interaction in complex scenarios suggests chatbots complement rather than replace human service. This research highlights the potential of AI-enabled chatbots to enhance customer experience, though their development must continue to focus on complex task management and personalised interactions.