Intelligent conversational agents (ICAs) are artificial intelligence (AI)-enabled systems that can communicate with humans through text or voice using natural language. The first ICA, “Eliza,” appeared in 1966 to simulate human conversation using pattern matching. Commercial ICAs appeared on the AOL and MSN platforms in 2001 and aided in developing advanced AI and Human-Computer Interaction (HCI). Since then, ICAs have progressively appeared in consumer products and services. Their success depends on the user’s experience and attitude towards these services. This research examines customer attitudes towards ICAs through a theoretical framework of integrated Expectation Confirmation Theory (ECT) and Task Technology Fit Theory (TTF). By exploring user experience via an experiment that engages end-users with ICA’s different functions and tasks, this study examines user perception of ICA’s AI capabilities, such as Conversation Ability, Friendliness, Intelligence, Responsiveness, Task Performance, and Trust. This research investigates how customer satisfaction with ICA capabilities and perceived task technology fit influence their intention to use ICAs. A field survey of 380 Canadian end-users utilizing ICAs on the websites of five large Canadian telecom service providers enabled empirical testing of the model. / Thesis / Doctor of Philosophy (PhD)