The proliferation of generative artificial intelligence (GAI) tools such as ChatGPT has catalyzed growing interest in their potential to support personalized learning (PL) in educational settings. While the promise of PL lies in tailoring instruction to individual learner needs, the integration of generative AI into such pedagogical models remains under-explored and insufficiently evaluated. This study presents a two-phase design-based research examining the affordances and limitations of ChatGPT as a tutor bot in facilitating PL among graduate students. Through interaction analysis, rubric-based performance assessment, and behavioral flow visualization, the study reveals that AI-driven tutoring can significantly enhance learner outcomes—especially when guided by structured prompts and pedagogically aligned designs. Findings underscore the dual importance of instructional design and real-time feedback quality in leveraging AI tools for effective, personalized learning experiences. The study contributes to the evolving discourse on human–AI partnerships in education and calls for deeper integration of learning science principles in the deployment of generative AI technologies.