Artificial Intelligence in Psychotherapy: A Review of the Effectiveness and Risks of Using AI Chatbots

Context and relevance. The growing implementation of artificial intelligence (AI) in sychotherapeutic practice is driven by the increasing need for effective, scalable, and accessible tools to support individuals with mental health conditions, including post-traumatic stress disorder (PTSD). Objective. This literature review aims to synthesize international empirical studies evaluating the effectiveness of AI chatbots in psychotherapy. Methods and materials. The analysis included 25 English-language publications examining these systems from clinical, methodological, and ethical perspectives. Results. The first thematic cluster addresses the therapeutic effectiveness of AI chatbots used either independently or alongside in-person therapy. Numerous studies report short-term reductions in symptoms of depression, anxiety, and PTSD, as well as increased patient engagement and emotional resilience. Adaptive and personalized AI systems, as well as hybrid models combining AI with human therapist involvement, are considered particularly promising. The second cluster highlights limitations, such as methodological heterogeneity, lack of long-term data, superficial diagnostic interactions, and potential safety risks in crisis situations. Issues of privacy, trust, the limits of AI autonomy, and the distribution of responsibility are also discussed. Conclusions. Overall, the review demonstrates the significant potential of AI chatbots in psychotherapy while emphasizing the need for further development, clinical validation, and ethical regulation to ensure their safe and effective use.

1. Birkun, A.A, Gautam, A. (2023). Large Language Model (LLM)-Powered Chatbots Fail to Generate Guideline-Consistent Content on Resuscitation and May Provide Potentially Harmful Advice. Prehospital and Disaster Medicine, 38(6), 757—763. https://doi.org/1017/S1049023X23006568
2. Busso, C., Collins, A., Monson, C., Fitzpatrick, S., Lenton-Brym, A., Kuo, J., Ouyang, J., Lane, J. (2024). Using machine learning to increase access to and engagement with trauma‐focused interventions for posttraumatic stress disorder. The British Journal of Clinical Psychology, 64(1), 125—136. https://doi.org/1111/bjc.12468
3. Chen, M., Serikawa, S., Li, Y., Kim, H. (2017). Brain Intelligence: Go beyond Artificial Intelligence. Mobile Networks and Applications, 23, 368—375. https://doi.org/1007/s11036-017-0932-8
4. Danieli, M., Ciulli, T., Mousavi, S.M., Silvestri, G., Barbato, S., Di Natale, L., Riccardi, G. (2022). Assessing the Impact of Conversational Artificial Intelligence in the Treatment of Stress and Anxiety in Aging Adults: Randomized Controlled Trial. JMIR Mental Health, 23(9), https://doi.org/10.2196/38067
5. Elbogen, E.B., Dennis, P.A., Van Voorhees, E.E., Blakey, S.M., Johnson, J.L., Johnson, S.C., Wagner, H.R., Hamer, R.M., Beckham, J.C., Manly, T., Belger, A. (2019). Cognitive Rehabilitation With Mobile Technology and Social Support for Veterans With TBI and PTSD: A Randomized Clinical Trial. Journal of Head Trauma Rehabilitation, 34(1), 1—10. https://doi.org/1097/HTR.0000000000000435
6. Farzan, M., Ebrahimi, H., Pourali, M., Sabeti, F. (2025). Artificial Intelligence-Powered Cognitive Behavioral Therapy Chatbots, a Systematic Review. Iran Journal of Psychiatry,20(1), 102—110. https://doi.org/18502/ijps.v20i1.17395
7. Fulmer, R., Joerin, A., Gentile, B., Lakerink, L., Rauws, M. (2018). Using Psychological Artificial Intelligence (Tess) to Relieve Symptoms of Depression and Anxiety: Randomized Controlled Trial. JMIR Mental Health, 5(4), https://doi.org/10.2196/mental.9782
8. Greer, S., Ramo, D.E., Chang, Y.J., Fu, M., Moskowitz, J., Haritatos, J. (2019). Use of the Chatbot “Vivibot” to Deliver Positive Psychology Skills and Promote Well-Being Among Young People After Cancer Treatment: Randomized Controlled Feasibility Trial. JMIR mHealth and uHealth, 7(10), e15018. https://doi.org/2196/15018
9. He, Y., Yang, L, Zhu, X., Wu, B., Zhang, S., Qian, C., Tian, T. (2022). Mental Health Chatbot for Young Adults With Depressive Symptoms During the COVID-19 Pandemic: Single-Blind, Three-Arm Randomized Controlled Trial. Journal of Medical Internet Research, 24(11), https://doi.org/10.2196/40719
10. He, Y., Yang, L., Qian, C., Li, T., Su, Z., Zhang, Q., Hou, X. (2023). Conversational Agent Interventions for Mental Health Problems: Systematic Review and Meta-analysis of Randomized Controlled Trials. Journal of Medical Internet Research,28(25), https://doi.org/10.2196/43862
11. Karkosz, S., Szymański, R., Sanna, K., Michałowski, J. (2024). Effectiveness of a Web-based and Mobile Therapy Chatbot on Anxiety and Depressive Symptoms in Subclinical Young Adults: Randomized Controlled Trial. JMIR Formative Research, 20(8), https://doi.org/10.2196/47960
12. Kian, M.J., Zong, M., Fischer, K., Singh, A., Velentza, A.-M., Sang, P., Upadhyay, Sh., Gupta, A., Faruki, M.A., Browning, W., Arnold, S.M.R., Krishnamachari,, Mataric, M.J. (2026). LLM-powered socially assistive robot-delivered cognitive behavioral therapy exercises: an exploratory study with university students. Frontiers in Robotics and AI, 13,article № 1802622 . https://doi.org/10.3389/frobt.2026.1802622
13. Kuhn, E., Kanuri, N., Hoffman, J.E., Garvert, D.W., Ruzek, J.I., Taylor, C.B. (2017). A randomized controlled trial of a smartphone app for posttraumatic stress disorder symptoms. Journal of Consulting and Clinical Psychology, 85(3), 267—273. https://doi.org/1037/ccp0000163
14. Trousset, V., Lefèvre, T. (2021). Artificial Intelligence in Medicine and PTSD. In: Lidströmer, N., Ashrafian, H. (Eds), Artificial Intelligence in Medicine. Springer, Cham. 1— https://doi.org/10.1007/978-3-030-58080-3_208-1
15. Li, H., Zhang, R., Lee, Y.C., Kraut, R.E., Mohr, D.C. (2023). Systematic review and meta-analysis of AI-based conversational agents for promoting mental health and well-being. NPJ Digital Medicine,6(1), Аrticle 236. https://doi.org/1038/s41746-023-00979-5
16. Liu, I., Xiao, Y., Liu, F., Wu, Sh., Ni, Sh. (2022). Assessing the Effectiveness of Using Chatbots for Positive Psychological Intervention: A Randomized Control Study. International Symposium of Chinese CHI,23, 227—234. https://doi.org/1145/3565698.3565789
17. Nov, O., Singh, N., Mann, D. (2023). Putting ChatGPT's Medical Advice to the (Turing) Test: Survey Study. JMIR Medical Education, 10(9), https://doi.org/10.2196/46939
18. Possemato, K., Kuhn, E., Johnson, E., Hoffman, J.E., Owen, J.E., Kanuri, N., De Stefano, L., Brooks, E. (2016). Using PTSD Coach in primary care with and without clinician support: a pilot randomized controlled trial. General Hospital Psychiatry, 38, 94—98. https://doi.org/1016/j.genhosppsych.2015.09.005
19. Rahsepar Meadi, M., Sillekens, T., Metselaar, S., van Balkom, A., Bernstein, J., Batelaan, N. (2025). Exploring the Ethical Challenges of Conversational AI in Mental Health Care: Scoping Review. JMIR Mental Health,21(12), e60432. https://doi.org2196/60432
20. Rzadeczka, M., Sterna, A., Stolinska, J., Kaczynska, P., Moskalewicz, M. (2025). The Efficacy of Conversational AI in Rectifying the Theory-of-Mind and Autonomy Biases: Comparative Analysis. JMIR Mental Health,7(12), e64396. https://doi.org/2196/64396
21. Schillings, C., Meissner, E., Erb, B., Bendig, E., Schultchen, D., Pollatos, O. (2023). Effects of a Chatbot-Based Intervention on Stress and Health-Related Parameters in a Stressed Sample: Randomized Controlled Trial. JMIR Mental Health, 11, e50454. https://doi.org/2196/50454
22. Scholich, T., Barr, M., Wiltsey Stirman, S., Raj, S. (2025). A Comparison of Responses from Human Therapists and Large Language Model-Based Chatbots to Assess Therapeutic Communication: Mixed Methods Study. JMIR Mental Health, 21(12), e69709. https://doi.org/2196/69709
23. Scott, S. (2007). Multiple Traumatic Experiences and the Development of Posttraumatic Stress Disorder. Journal of Interpersonal Violence, 22,932—938. https://doi.org/1177/0886260507301226
24. Son, Y., Clouston, S.A.P., Kotov, R., Eichstaedt, J.C., Bromet, E.J., Luft, B.J., Schwartz, H.A. (2023). World Trade Center responders in their own words: predicting PTSD symptom trajectories with AI-based language analyses of interviews. Psychological Medicine, 53(3),918—926. https://doi.org/1017/S0033291721002294
25. Sprang, K., Watkins, L., Rothbaum, B. (2018). Treating PTSD: A Review of Evidence-Based Psychotherapy Interventions. Frontiers in Behavioral Neuroscience, 12, Аrticle 258. https://doi.org/3389/fnbeh.2018.00258
26. Vaidyam, A.N., Linggonegoro, D., Torous, J. (2021). Changes to the Psychiatric Chatbot Landscape: A Systematic Review of Conversational Agents in Serious Mental Illness: Changements du paysage psychiatrique des chatbots: une revue systématique des agents conversationnels dans la maladie mentale sérieuse. The Canadian Journal of Psychiatry, 66(4), 339—348. https://doi.org/1177/0706743720966429
27. Vali, M., Kovács, L., Motahari-Nezhad, H., Gandomi, A. (2025). Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis. BMC Medical Informatics and Decision Making,25, Аrticle  https://doi.org/10.1186/s12911-024-02754-2
28. Wah, J.N.K. (2025). Revolutionizing e-health: the transformative role of AI-powered hybrid chatbots in healthcare solutions. Frontiers in Public Health,13(13), https://doi.org/ 10.3389/fpubh.2025.1530799
29. Wan, R., Wan, R., Chen, J., Hu, A., Xie, W., Liu, Y., Xie, Q. (2024). Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis. Behavioral Sciences,15(1), Аrticle 27. https://doi.org/3390/bs15010027
30. Wang, L., Qing, Q., Xia, F., Bai, X., Liu, J., Kong, X., Lee, I. (2018). Artificial Intelligence in the 21st Century. IEE Access,6, 34403—34421. https://doi.org/1109/ACCESS.2018.2819688
31. Yau, J.Y., Saadat, S., Hsu, E., Murphy, L.S., Roh, J.S., Suchard, J., Tapia, A., Wiechmann, W., Langdorf, M.I. (2024). Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study. Journal of Medical Internet Research,4(26), https://doi.org/10.2196/60291