Depression is prevalent and incapacitating mental health ailment, distressing more than 300 million lives, reported by World Health Organization. Poses significant challenges to public health systems worldwide. In the United States alone, 29.0% of adults reported a lifetime diagnosis of depression by 2023, marking a substantial increase from previous years. The critical need for early detection and intervention is underscored by depression’s role as a leading factor of suicidal death, predominantly among young adults. The integration of AI and mental health research, mostly in depression detection at initial stage, represents a paradigm shift in the field of psychiatry and psychology. This abstract synthesizes current research on AI’s transformative potential, its challenges, and the ethical considerations that accompany its implementation in mental health. We have considered around 60 good, authentic, peer-reviewed articles from popular conferences and journals. The screening process of the journals has been segregated through subject relativity, the aim of the study. This study explores the current trend in depression detection and what are the challenges so that new researchers can find a roadmap.