Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{187523,
        author = {ANUSKA KUMARI and Dr. Goldi soni and Khushi soni},
        title = {The Role of Artificial Intelligence in Mental Health},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {5361-5367},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=187523},
        abstract = {Artificial Intelligence (AI) is revolutionizing mental healthcare by providing advanced tools for early diagnosis, personalized treatment, and real-time monitoring. The integration of AI-powered machine learning models, chatbots, predictive analytics, and digital therapy platforms is enhancing accessibility and efficiency in mental health services. AI-driven systems can analyze speech patterns, facial expressions, physiological data, and social media interactions to detect early signs of mental health conditions, offering timely interventions and improving patient outcomes.The use of AI chatbots and virtual therapists is expanding the reach of mental healthcare, particularly for underserved populations, by providing 24/7 support and cognitive behavioral therapy (CBT) interventions. Additionally, AI-based predictive analytics helps clinicians anticipate relapses in conditions like depression, bipolar disorder, and schizophrenia. AI-powered wearable devices and IoT sensors continuously monitor physiological indicators such as sleep patterns and heart rate variability, contributing to comprehensive mental health assessments. Despite these advancements, the implementation of AI in mental health poses significant challenges, including concerns over data privacy, algorithmic bias, ethical considerations, and lack of regulatory oversight. The reliability and fairness of AI-driven diagnoses remain a subject of debate, as biased training datasets can lead to disparities in mental health predictions. Moreover, the explainability and transparency of AI models are crucial to ensuring trust and acceptance among healthcare professionals and patients alike.
This paper provides an in-depth analysis of AI applications, ethical dilemmas, technological advancements, and future prospects in the field of mental health. By exploring real-world case studies and emerging trends, this study underscores the importance of AI as an assistive tool rather than a replacement for mental health professionals.
The research further advocates for the integration of explainable AI (XAI), blockchain-based security solutions, and regulatory frameworks to ensure ethical and responsible AI adoption in mental healthcare. Ultimately, AI has the potential to create a patient-centric, transparent, and secure mental health ecosystem that prioritizes accessibility, efficiency, and ethical integrity.},
        keywords = {Mental Health, Artificial Intelligence, Ethics, Machine Learning, Diagnosis, Digital Therapy, Predictive Analytics},
        month = {November},
        }