AI-Driven Mental Health Chatbots and Their Impact on Anxiety and Depression Among College Students

Anxiety and depression remain among the most prevalent mental health conditions, creating increasing demands on mental health care systems and motivating the exploration of artificial intelligence (AI)–based solutions. This article examines the current state of AI applications for the detection, monitoring, and support of anxiety and depressive disorders by synthesizing peer-reviewed literature identified through structured searches of major academic databases. The examined studies demonstrate that AI has been applied across multiple functions, including symptom identification, risk stratification, and the delivery of low-intensity psychological support. While several investigations report promising outcomes related to accessibility and early detection, findings are highly variable and constrained by methodological heterogeneity, limited external validation, and short follow-up periods. The evidence further highlights challenges related to interpretability, ethical accountability, data governance, and equitable implementation. The findings suggest that AI-driven mental health tools may enhance existing care models when deployed as complementary supports rather than standalone solutions. Continued progress in this field will depend on rigorous evaluation, transparent governance, and careful integration of AI systems within established mental health care pathways.