Artificial Intelligence and Cognitive Behavioral Therapy: A New Direction in Mental Health Care - A Systematic Literature Review

Abstract

Artificial Intelligence (AI) is transforming mental healthcare by improving the accessibility, personalization, and efficiency of psychological interventions. Among various psychotherapeutic approaches, Cognitive Behavioral Therapy (CBT) has emerged as one of the most suitable frameworks for AI integration due to its structured, evidence-based nature. This systematic literature review (SLR) synthesizes current evidence on the application of AI in CBT, with particular emphasis on conversational agents, machine learning, natural language processing (NLP), and personalized mental health interventions. The review was conducted following the PRISMA 2020 guidelines, using peer-reviewed studies retrieved from Scopus, PubMed, Web of Science, PsycINFO, IEEE Xplore, and ScienceDirect. Studies published between 2015 and 2025 that examined AI-assisted CBT interventions for mental health were included. The findings indicate that AI-powered chatbots and intelligent decision-support systems can effectively deliver psychoeducation, cognitive restructuring, behavioural activation, and continuous symptom monitoring, leading to improvements in depression, anxiety, stress, and treatment engagement. However, challenges related to data privacy, algorithmic bias, explainability, and the limited ability of AI to establish therapeutic relationships remain significant barriers to widespread clinical implementation. The review concludes that AI should complement rather than replace mental health professionals. Future research should focus on explainable AI, culturally adaptive interventions, long-term clinical evaluation, and ethically responsible deployment of AI-assisted psychotherapy.