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Articles | Applied Psychology and Cognitive Science | Volume 1 - Issue 1 - 2026 | 1−13 |
© 2026 by the author(s), and is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License Creative Commons Attribution 4.0 International (CC BY 4.0) License

Artificial Intelligence in Psychological Practice: A Systematic Review of Opportunities, Challenges, and Ethical Considerations

Author(s): Rizky Aditya Pranawa , Nabila Ayu Kurniasari
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Universitas Muhammadiyah Palu, Jalan H. M. Rusdy Toana No. 1, Mantikulore, Palu 94118, Indonesia

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Applied Psychology and Cognitive Science

Volume 1 - Issue 1 - 2026

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Artificial intelligence (AI) is increasingly reshaping psychological practice by extending the capabilities of clinical assessment, personalized intervention, decision support, and continuous behavioral monitoring. This systematic review critically synthesized current evidence on the clinical opportunities, implementation barriers, and ethical implications associated with the integration of AI into psychological care. Contemporary applications encompassed machine learning models for diagnostic screening and suicide risk prediction, conversational agents delivering cognitive behavioral therapy, clinician decision support systems, and digital phenotyping through smartphones and wearable sensors. Evidence from randomized controlled trials and systematic reviews suggested that AI assisted interventions could enhance accessibility, scalability, patient engagement, and outcomes related to depressive symptoms. However, evidence regarding anxiety, stress, and other psychological outcomes remained heterogeneous, limiting definitive conclusions regarding clinical effectiveness. Translation into routine psychological practice was further constrained by small and insufficiently representative datasets, limited external and prospective validation, algorithmic bias, inadequate model interpretability, uncertain clinical accountability, workforce readiness, and concerns regarding potential disruption of therapeutic relationships. Ethical and governance challenges were particularly prominent and included privacy, data security, informed consent, transparency, accountability, equitable access, and compliance with rapidly evolving regulatory frameworks. Collectively, the evidence indicated a substantial gap between technological capability and clinically validated implementation. Future research should prioritize representative and culturally diverse datasets, prospective multicenter validation, longitudinal evaluation of clinical outcomes, systematic assessment of algorithmic bias, and interdisciplinary collaboration among psychologists, AI developers, healthcare institutions, policymakers, and regulators. Rather than functioning as a substitute for psychological expertise, AI should be positioned as an augmentative clinical tool operating within clearly defined professional and ethical boundaries. Responsible integration therefore requires a human centered framework in which clinical judgment, therapeutic relationships, patient autonomy, transparent governance, and robust ethical safeguards remain central to psychological care.

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SUBMITTED: 10 August 2026
ACCEPTED: 02 October 2026
PUBLISHED: 26 October 2026
SUBMITTED to ACCEPTED: 54 days

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