ArticleFrontiers in psychology2026
Artificial intelligence in the psychologist's toolkit: Psypilot as a case study.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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5 authors.
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Abstract
Artificial intelligence (AI) is rapidly reshaping how psychology is practiced, from assessment and case formulation to intervention planning, monitoring, and documentation. Yet the field faces a strategic choice: deploy AI as a substitutive "automated therapist," or develop AI copilots that augment psychologists' judgment while preserving the relational and ethical core of professional work. In this article, we synthesize how contemporary AI-especially Machine Learning and Large Language Models- maps onto psychologists' core tasks and discuss the implications for clinical quality, scalability, and innovation in real-world settings. We then present Psypilot as a case study of the copilot paradigm: an AI-powered clinical assistance platform designed to support Precision Mental Health. We critically examine key risks and governance challenges such as automation bias, data representativeness and fairness, privacy and secondary use, transparency, and accountability under emerging regulatory frameworks, and translate them into practical design and training recommendations. By framing AI as workflow-embedded decision support rather than autonomous care, this contribution advances responsible innovation and clarifies the competencies psychologists need to thrive in an AI-driven professional landscape.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.