As artificial intelligence (AI) tools become increasingly integrated into educational settings, understanding how they align with learners’ needs and support meaningful engagement has become a research priority. Among emerging AI tools, Google’s NotebookLM offers a novel, multimodal learning experience that allows students to interact with personalized content through summaries, podcasts, mind maps, and simulated dialogues. However, empirical evidence on its effectiveness from the learner’s perspective remains limited. This quantitative study examines the effectiveness of NotebookLM in enhancing student engagement and perceived academic performance, utilizing the Task-Technology Fit (TTF) model as a theoretical framework. The study involved a convenience sample of 61 third-year undergraduate students from a university in Saudi Arabia who used NotebookLM to study project management course materials. Data were collected using a structured questionnaire with measurement items adapted from previously validated in