Artificial Intelligence applied to psychology: the example of Psypilot  as a therapeutic co-pilot

Authors

DOI:

https://doi.org/10.70478/apuntes.psi.2026.44.09

Keywords:

Artificial intelligence, Precision mental health, Data-driven decision-making, Measurement-based care

Abstract

Artificial Intelligence (AI) is transforming psychological practice, reaching a strategic crossroads where “automated therapists” are being deployed alongside “digital co-pilots” to enhance clinical judgement without compromising the professional bond. This article summarizes the applications of AI in psychology, from assessment to documentation, analyses its practical implications for the quality of care. Unlike substitute AI models, the case study of Psypilot (https://psypilot.com) is presented as an example of implementing a therapeutic co-pilot to support professional work, demonstrating how to implement the Precision Mental Health paradigm in clinical practice. Finally, the article examines governance challenges and ethical dilemmas, proposing an ethical framework in which technology supports clinical decision-making. The conclusion is that the future of the profession lies not in technological resistance, but in acquiring new skills and becoming algorithmically literate.

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References

Bickman, Leonard (2020). Improving mental health services: A 50-year journey from randomized experiments to artificial intelligence and precision mental health. Administration and Policy in Mental Health and Mental Health Services Research, 47(5), 795-843. https://doi.org/10.1007/s10488-020-01065-8

Boucher, Eliane M.; Harake, Nicole R.; Ward, Haley E.; Stoeckl, Sarah E.; Vargas, Junielly; Minkel, Jared; Parks, Acacia C. y Zilca, Ran (2021). Artificially intelligent chatbots in digital mental health interventions: A review. Expert Review of Medical Devices, 18, 37-49. https://doi.org/10.1080/17434440.2021.2013200

Cohen, Zachary D. y DeRubeis, Robert J. (2018). Treatment selection in depression. Annual Review Clinical Psychology, 14, 209-236. https://doi.org/10.1146/annurev-clinpsy-050817-084746

Constantino, Michael J.; Boswell, James F.; Coyne, Alice E.; Swales, Thomas P. y Kraus, David R. (2021). Effect of matching therapists to patients vs assignment as usual on adult psychotherapy outcomes: A randomized clinical trial. JAMA Psychiatry, 78(9), 984-993. https://doi.org/10.1001/jamapsychiatry.2021.1221

Dwyer, Dominic B.; Falkai, Peter y Koutsouleris, Nikolaos. (2018). Machine Learning approaches for clinical psychology and psychiatry. Annual Review of Clinical Psychology, 14(1), 91-118. https://doi.org/10.1146/annurev-clinpsy-032816-045037

Esteva, Andre; Kuprel, Brett; Novoa, Roberto A.; Ko, Justin; Swetter, Susan M.; Blau, Helen M. y Thrun, Sebastian (2017). Dermatologist-level classification of skin cancer with deep neural networks. Nature, 542(7639), 115-118. https://doi.org/10.1038/nature21056

European Parliament (2024). Artificial Intelligence Act: (2024)0138. European Union. https://artificialintelligenceact.eu/wp-content/uploads/2024/04/TA-9-2024-0138_EN.pdf

Gerke, Sara; Minssen, Timo y Cohen, Glenm (2020). Ethical and legal challenges of artificial intelligence-driven healthcare. En: Adam Bohr y Kaveh Memarzadeh (Eds.), Artificial Intelligence in Healthcare (pp. 295-336). Academic Press. https://doi.org/10.1016/B978-0-12-818438-7.00012-5

Johns, Robert G.; Barkham, Michael; Kellett, Stephen y Saxon, David (2019). A systematic review of therapist effects: A critical narrative update and refinement to Baldwin and Imel’s (2013) review. Clinical Psychology Review, 67, 78-93 . https://doi.org/10.1016/j.cpr.2018.08.004

Lawrence, Hanna R.; Schneider, Renee. A.; Rubin, Susan B.; Matarić, Maja J.; McDuff, Daniel J. y Jones Bell, Megan (2024). The opportunities and risks of large language models in mental health. JMIR Mental Health, 11, e59479. https://doi.org/10.2196/59479

Le Glaz, Aziliz; Haralambous, Yanis; Kim-Dufor, Deok-Hee; Lenca, Philippe; Billot, Romain; Ryan, Taylor C.; Marsh, Jonathan; DeVylder, Jordan; Walter, Michel; Berrouiguet, Sofian y Lemey, Christophe (2021). Machine learning and natural language processing in mental health: Systematic review. Journal of Medical Internet Research, 23(5), e15708. https://doi.org/10.2196/15708

Leaning, Imogen E.; Ikani, Nessa; Savage, Hanna S.; Leow, Alex; Beckmann, Christian; Ruhé, Henricus. G. y Marquand, Andre F. (2024). From smartphone data to clinically relevant predictions: A systematic review of digital phenotyping methods in depression. Neuroscience & Biobehavioral Reviews, 158, 105541. https://doi.org/10.1016/j.neubiorev.2024.105541

Lee, Ellen E.; Torous, John; De Choudhury, Munmun; Depp, Colin A.; Graham, Sarah A.; Kim, Ho-Cheol; Paulus, Martin P.; Krystal, John H. y Jeste, Dilip V. (2021). Artificial intelligence for mental health care: Clinical applications, barriers, facilitators, and artificial wisdom. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 6(9), 856-864. https://doi.org/10.1016/j.bpsc.2021.02.001

Lutz, Wolfgang; Vehlen, Antonia y Schwartz, Brian (2024). Data-informed psychological therapy, measurement-based care, and precision mental health. Journal of Consulting and Clinical Psychology, 92(10), 671-673. https://doi.org/10.1037/ccp0000904

Lutz, Wolfgang; Schwartz, Brian; Vehlen, Antonia; Eberhardt, Steffen T. y Delgadillo, Jaime (2025). Advances in personalization of psychological interventions. World Psychiatry: Official Journal of the World Psychiatric Association (WPA), 24(3), 343-345. https://doi.org/10.1002/wps.21342

McKinney, Scott M.; Sieniek, Marcin; Godbole, Varum; Godwin, Jonathan; Antropova, Natasha; Ashrafian, Hutan; Back, Trevor; Chesus, Mary; Corrado, Greg S.; Darzi, Ara; Etemadi, Mozziyar; Garcia-Vicente, Florencia; Gilbert, Fiona J.; Halling-Brown, Mark; Hassabis, Demis; Jansen, Sunny; Karthikesalingam, Alan; Kelly, Christopher. J.; King, Dominic; Ledsam, Joseph R.; Melnick, David; Mostofi, Hormuz; Peng, Lily; Reicher, Joshua J.; Romera-Paredes, Bernardino; Sidebottom, Richard; Suleyman, Mustafa; Tse, Daniel; Young, Kenneth C.; De Fauw, Jeffrey y Shetty, Shravya (2020). International evaluation of an AI system for breast cancer screening. Nature, 577(7788), 89-94. https://doi.org/10.1038/s41586-019-1799-6

Olson, Kristine D.; Meeker, Daniela; Troup, Matt; Barker, Timothy. D.; Nguyen, Vinh H.; Manders, Jennifer B.; Stults, Cheryl D.; Jones, Veena G.; Shah, Sachin D.; Shah, Tina y Schwamm, Lee H. (2025). Use of ambient AI scribes to reduce administrative burden and professional burnout. JAMA Network Open, 8(10), e2534976. https://doi.org/10.1001/jamanetworkopen.2025.34976

Putica, Andrea; Khanna, Rahul; Bosl, William; Saraf, Sudeep y Edgcomb, Juliet (2025). Ethical decision-making for AI in mental health: The Integrated Ethical Approach for Computational Psychiatry (IEACP) framework. Psychological Medicine, 55, e213. https://doi.org/10.1017/S0033291725101311

Roca, Pablo (2025). ¿Puede una mente artificial sanar una mente natural? Aplicaciones de la inteligencia artificial en psicología. En José M. Ortiz-Ibarz y Jaime Benguría-Aguirreche (Coords.), Un nuevo conocimiento transversal: la inteligencia artificial aplicada (pp. 145-165). Tirant lo Blanch.

Russell, Stuart y Norvig, Peter (2020). Artificial Intelligence: A Modern Approach (4th Ed.). Pearson.

Sahu, Mehar; Gupta, Rohan; Ambasta, Rashmi. K. y Kumar, Pravir (2022). Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis. Progress in Molecular Biology and Translational Science, 190, 57-100. Elsevier. https://doi.org/10.1016/bs.pmbts.2022.03.002

Schaffrath, Jana; Weinmann-Lutz, Birgit y Lutz, Wolfgang (2022). The Trier Treatment Navigator (TTN) in action: Clinical case study on data-informed psychological therapy. Journal of Clinical Psychology, 78(10), 2016-2028. https://doi.org/10.1002/jclp.23362

Scodari, Bruno T.; Chacko, Sarah; Matsumura, Rina y Jacobson, Nicholas C. (2023). Using machine learning to forecast symptom changes among subclinical depression patients receiving stepped care or usual care. Journal of Affective Disorders, 340, 213-220. https://doi.org/10.1016/j.jad.2023.08.004

Shatte, Adrian B.R.; Hutchinson, Delyse M. y Teague, Samantha J. (2019). Machine learning in mental health: A scoping review of methods and applications. Psychological Medicine, 49(09), 1426-1448. https://doi.org/10.1017/S0033291719000151

Spittal, Matthew. J.; Guo, Xianglin Aneta; Kang, Laurant; Kirtley, Olivia J.; Clapperton, Angela; Hawton, Keith; Kapur, Nav; Pirkis, Jane y Carter, Greg (2025). Machine learning algorithms and their predictive accuracy for suicide and self-harm: Systematic review and meta-analysis. PLOS Medicine, 22(9), e1004581. https://doi.org/10.1371/journal.pmed.1004581

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Published

08/06/2026

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Section

Research articles

How to Cite

Roca, P., Sánchez-Pedreño, M., Rodríguez-Fernández, G., García del Valle, E. P., & Zangri, R. M. (2026). Artificial Intelligence applied to psychology: the example of Psypilot  as a therapeutic co-pilot. Apuntes De Psicología, 44(2), 77-84. https://doi.org/10.70478/apuntes.psi.2026.44.09

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