Abstract
Mental health disorders remain a critical global health concern, significantly contributing to disease burden and economic impact. Conventional therapeutic systems often fail to meet the rising demand for timely and accessible mental healthcare. This paper presents a systematic review of Artificial Intelligence-enabled chatbots in mental health, highlighting their potential to enhance support delivery. By integrating Natural Language Processing (NLP), sentiment analysis, and emotion recognition, these systems provide scalable, real-time, and stigma-free assistance. The study analyses chatbot architectures, underlying technologies, functionalities, benefits, and ethical considerations. Findings indicate that AI-driven chatbots improve accessibility, enable early intervention, and support continuous care. However, they are best utilized as complementary tools alongside professional mental health services.
Keywords
Artificial Intelligence, Chatbots, Mental Health, NLP, Sentiment Analysis, Healthcare Technology, Digital Therapeutics
Citations
IRE Journals:
Komal , Khushi Rajput, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri "Artificial Intelligence-Enabled Chatbots in Mental Health: A Systematic Review" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 1999-2007 https://doi.org/10.64388/IREV9I10-1716482
IEEE:
Komal , Khushi Rajput, Dr. Ishrat Ali, Prof. (Dr.) Sanjay Pachauri
"Artificial Intelligence-Enabled Chatbots in Mental Health: A Systematic Review" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716482
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