AI has recently shown immense potential in positively reshaping the landscape of higher education at multiple levels. Often referred to as AIED, AI in education is no longer a futuristic concept. Ongoing research investigates the right adoption of GenAI for diverse educational processes, including assessment. The present chapter deals with AI-supported FA (Formative Assessment) through the lens of feedback as a core component of FA. To this aim, we tested the implementation of a customized bot that we named “Intellectus”, and which was supplied with the educator’s course material to ensure that the generated feedback is both relevant and course-aligned. To achieve the required results, the study in this chapter adopts a quantitative research design using a structured questionnaire adapted from DeLone & McLean Information System Success Model framework with a focus on three main constructs: SQ (System Quality), AFQ (Assessment Feedback Quality), and IFU (Intended Future Use). Data was collected from 75 undergraduate students of the Higher School of Teachers, Moulay Ismail University, and analyzed using Python. Findings of this study revealed high perceptions of both system and assessment feedback quality. Participants have also expressed very positive intentions to opt for personalized bots (if available) for future subjects.