The research aims to study the perceptions of users, i.e., learners and faculties, regarding the usability and effectiveness of AI-driven automated grading and feedback systems (AI-AGFS) within online learning management systems (LMS). The study targets adult learners engaged in online learning for personal or career advancement alongside their professional work. The primary objective is to establish the relationship between the components of AI-AGFS and different user experience factors, perceived usefulness, and ease of use per TAM, to understand user preferences and expectations from an application usability perspective. The components of AI-AGFS include automated grading, real-time feedback, personalized recommendations, and customizations. The study results provide an overview of the factors that the learners would like to have in the AI system and from an overall perspective ease of use is something that the users perceive to be significantly predominant. The major findings based on the regression analysis conducted is that while the questionnaire does capture the essence of the need of AI-AGFS and its factors, there might be some factors which are either duplicating or missed out and can be further researched upon. The results can help universities or LMS vendors work towards optimizing the experiences of users and engage them on a continuous basis thereby promoting the usage of online learning environments.