People above 60 years of age have difficulties using laptops and digital healthcare systems because of eyesight problems, hand tremors, and less exposure to laptops. The needs are not met using traditional means of communication, including intricate website interfaces and conventional chatbots, which leads to poor healthcare participation. Standard digital interfaces are not customizable; they lack adjustable font density and are not voice-controlled, which are important aspects for the elderly. Further, the existing icon-based or text-based chatbots are less efficient in handling and responding to complicated healthcare-related queries. To this end, the following work seeks to design an AI-based interface for a chatbot to support elderly patients for timely appointments and efficient follow-up. It employs machine learning and natural language processing algorithms to make it more sensitive to patients’ needs. The features installed in the improved chatbot are options for text size, voice control, booking an appointment, asking for any medical data, and prescription prompts. It also updates the current user’s interactions, allowing the dynamic adjustment of the interface and more effective answering of multipart questions. Similarly, the presence of older users in usability testing showed that Older adults’ usability effects can be observed in terms of increased number of successful task completion, perceived satisfaction, and overall quality of interaction. Thus, the iterative approach based on direct user feedback in the context of the current work allowed for the overcoming of such drawbacks and the provision of the target population of older adults with the needed healthcare services.