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Mary Patricia Nithilan is an Assistant Professor in the Department of BBA General at Loyola Academy Degree and PG College, Secunderabad, Telangana, India. Her academic role is associated with business administration education. Her contribution to this chapter examines AI-based approaches to mental health, stress management, and well-being prediction.
Mental health, psychological strain, and individual wellness have emerged as significant issues within educational establishments, professional environments, healthcare frameworks, and societal groups. Traditional mental health evaluation techniques frequently rely on self-reported surveys, therapeutic discussions, and intermittent assessments, which may fail to reflect ongoing fluctuations in a person's emotional and psychological condition. Artificial intelligence (AI) provides avenues for examining various data sources, recognising probable stress patterns, and facilitating early mental health evaluations via sophisticated predictive systems. Machine learning, deep learning, natural language processing, wearable sensing, and multimodal data analytics can be employed to analyse behavioural, physiological, environmental, and linguistic markers linked to stress and well-being. It additionally addresses explainable artificial intelligence, privacy-preserving methodologies, equity, human supervision, and ethical implementation. Ultimately, novel research trajectories such as individualised forecasting, federated learning, multimodal foundational models, and context-sensitive digital mental health frameworks are evaluated. The chapter establishes a thorough basis for creating dependable, ethical, and user-focused AI solutions that promote mental health awareness, early intervention, and overall well-being.