PERSPECTIVE article
Front. Psychol.
Sec. Psychology for Clinical Settings
This article is part of the Research TopicPsychology, AI, and Innovation: Transforming Science, Education, and Professional PracticeView all articles
Artificial Intelligence in the psychologist's toolkit: Psypilot as a case study
Provisionally accepted
Pablo Roca1,2*
Rosaria Maria Zangri2,3Guillermo Rodriguez-Fernandez2Martin Sanchez-Pedreño1,2Eduardo Pantaleon Garcia del Valle2,4- 1Universidad Villanueva, Madrid, Spain
- 2Medea Lab, Madrid, Spain
- 3unie Universidad, Madrid, Spain
- 4IE University, Madrid, Spain
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
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.
Keywords: AI, artificial intelligence, Clinical decision support, Large language models, Measurement-based care, precision mentalhealth
Received: 03 Jan 2026; Accepted: 12 Feb 2026.
Copyright: © 2026 Roca, Zangri, Rodriguez-Fernandez, Sanchez-Pedreño and Garcia del Valle. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Pablo Roca
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.