The high prevalence of deteriorating mental health among university students, driven by stress, is a pressing concern. One significant stressor is poor time management, which directly affects students’ academic success and overall well-being. Despite providing counseling services and time management resources, the scale of the problem is causing academic institutions to fall short of meeting the demand. To alleviate this situation, this study seeks to evaluate the role of scalable systems like Large Language Model (LLM) based chatbots. The focus of the study is to compare how users perceive stress and time management advice generated by a LLM versus that extracted from a book authored by an expert. The study utilized GPT-4, a leading LLM, whose advice was evaluated by seventy participants. These participants perceived GPT-4’s advice as more practical and better explained compared to the book’s recommendations. For practicality, GPT-4’s advice scored better with 73% rating it as practical or highly practical versus only 68% giving that rating for the book’s advice (t = 2.87, p < 0.01). Similarly, for the well-explained variable, 88% of LLM’s guidance were rated as clear or very clear, exceeding the book’s 79% (t = 4.437, p < 0.01). This study highlights AI’s ability in giving effective advice that can be extended to a full coaching engagement. Such capabilities would not only augment human coaching but also address scalability challenge and expand accessibility.