A recent report says that one in every eight people worldwide lives with mental health conditions. Individuals, however, give least preference to mental health concerns either due to stigma or the belief that things will change in due course of time.
According to WHO, Psychiatric and substance use disorders have increased by 13% over the last decade. There is, however, a huge gap in diagnosis, treatment access and societal support. In a country like India where the population is huge, accessibility to mental health becomes a million dollar question.
AI in mental health
The amalgamation of AI in mental health has grown dramatically over the past decade, with usage among mental health professionals increasing from approximately 10% in 2015 to over 60% by 2024. This swift adoption echoes both the increasing global demand for mental health services and the maturation of AI technologies capable of meaningful clinical applications.
The DL and ML model opened a new avenue to understand mental health diagnosis and treatment. Recent systematic reviews have examined 85 studies demonstrating AI’s effectiveness across diagnosis, monitoring, and intervention domains, providing robust evidence for its potential to transform psychological practice. We stand at the verge of a technological revolution that opens up the avenues to address enduring challenges in mental health service provision while simultaneously raising critical ethical questions that demand our careful consideration.
What data says about India
In the Indian context, this revolution is particularly significant. With a doctor-patient ratio of 1:834 and only 0.75 psychiatrists per lakh citizens, India faces acute mental health service personnel shortages. The government allocates merely 0.06% of its total healthcare budget to mental health, creating unprecedented pressure for innovative solutions.
Research conducted in 2023 on 787 medical students from North India revealed alarming statistics: 37.2% had considered suicide, 10.9% had intentions to do so, and 3.3% had attempted it, underscoring the urgency of expanding mental health service delivery through technological innovation. This new AI technological revolution helps in recording individual cognitive and emotional changes and can keep daily track of the same. This in turn will help the individual to monitor and maintain mental health conditions and to use appropriate psychological interventions.
AI-powered medical interviews
Psychological assessment is one of the important applications in Psychology. Latest research has confirmed that AI-powered medical interviews using large language models can conduct structured assessments aligned with DSM-5 diagnostic criteria. These tools can identify subtle patterns in speech, facial expressions, and behavioral data that may escape human observation.
Reviews published in Nature Medicine have revealed that modern-day AI systems can analyse language or communication patterns and online activity to identify signs of depression or anxiety with up to 90% accuracy. In another study it was found that 70 university students had reduced symptoms of anxiety and depression after using an AI bot for Cognitive Behaviour therapy. In another study participants had reported less sadness, anger and anxiety after using virtual reality Dialectical Behaviour Therapy.
Using advanced DL model AI leverages techniques like Natural Language Processing (NLP) to assess mental health risks by analysing speech or text identifying signs of depression, anxiety or suicidal ideation. Vocal biomarkers in individual conversation help to flag potential risks.
Comprehensive diagnostics
Mental disorder predictive analysis in AI is reshaping the use of AI in mental health care by fostering mental health conditions before the symptoms fully emerge. By analysing data sets like electronic data sets, health records, genetic data, AI in behavioural health can identify risk factors for disorders such as schizophrenia.
AI diagnostic tools normally apply standardised outcome measures such as the Patient Health Questionnaire (PHQ-8, PHQ-9) and Generalised Anxiety Disorder scale (GAD-7) to ensure clinical validity and reliability. When this is combined with physiological testing of biomarkers and emotional/cognitive changes provide more comprehensive diagnosis than traditional methods of clinical interviewing.
Chatbots and virtual therapies deliver evidence based therapeutic techniques including CBT, mindfulness practices and emotional regulation strategies. This also offers immediate support during crisis moments before the arrival of clinician and acts as psychological first aid.
The skeptics
Though AI has been used in many fields, in mental health care only 10% of the mental health professionals use AI, that too only basic chatbots. A recent survey conducted in Chennai indicated that mental health practitioners are unaware of many AI tools. They are neither using these tools for assessment nor for intervention. It is reported by them that ethics becomes a concern while using AI tools. And many of the mental health professionals are skeptical about the efficacy of AI over traditional conversational methods.
Despite these promising developments, AI integration in Psychology raises profound ethical concerns that cannot be ignored. Systematic reviews have identified 18 key ethical considerations, including privacy and confidentiality, informed consent, bias and fairness, transparency and accountability, autonomy and human agency, and safety.
Curriculum designing
Students who are doing their Masters in Clinical Psychology can be trained to use AI for the assessments of psychological disorders such as depression, schizophrenia, OCD, and more.
Similarly those who specialise in Counselling should be trained in using AI for therapeutic processes like CBT, DBT etc. For organisational specialisation AI can be used for training need assessments, employee training and employee engagement.
AI can be used in criminal profiling and voice/ speech pattern recognition of criminals by forensic psychologists. Higher Education Institutions should modify their curriculum by incorporating AI in the courses like psychological assessment, psychotherapy, training and development. The data psychology course should be made compulsory so that the students apply the data driven method for a better understanding of human behaviour, cognition and emotions.
The integration of AI in psychology is not merely a technical challenge but a profound ethical and professional responsibility. By approaching this transformation with both enthusiasm for innovation and commitment to core values, we ensure that AI enhances the well-being of individuals with mental health conditions while safeguarding their privacy, autonomy, and access to equitable, compassionate care.
(U. Vijayabanu is an Assistant Professor (Senior), Department of Psychology, VIT Chennai)
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Published – November 14, 2025 06:12 pm IST
