Volume 6 • Issue 2 • PP: 25– 32 • 2026
Practical Implementation of Artificial Intelligence in Mental Healthcare: An Integrative Review of Approaches and Case Studies
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Artificial Intelligence in mental healthcare is a revolution in the delivery, evaluation and administration of mental health services. This review also maps current literature covering the practical application of AI in mental health practice, focusing on the descriptive use and specific integration and case analyses of those technologies in context. AI solutions are as follows: Solutions that assist with the diagnosis of psychiatric patients, as well as solutions enabled by artificial Intelligence that foretell situations of severe mental health emergencies of individual citizens. Some good examples, Like the REACH VET program, show how AI, using EHRs, can identify suicidal veterans’ risk and prevent potential suicides. Nevertheless, numerous challenges exist when using AI in mental health, such as workers’ resistance, ethical questions about patient data, and clinician engagement. Concerning implementation methodology, this review has incorporated ideas from implementation science, showing the need to employ a guided approach when implementing AI technologies in clinical practice. Based on the study results, there is potential for increasing patient outcomes through artificial Intelligence and group-specific treatment options, better tools for diagnosing diseases and practical cooperation, but constant work of technologists, clinicians, and policymakers will be needed to eliminate existing issues and ensure equal access to innovations in the sphere of mental health.
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