Technical debt in AI-enabled software development and its sociotechnical impact: A systematic literature review

DOI: https://doi.org/10.29375/25392115.5072
Keywords: Technical debt, Sociotechnical debt, Artificial intelligence, AI-enabled software
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Abstract

Artificial Intelligence – IA frameworks are being used to develop innovative software quickly, although these shortcuts could bring with them Artificial Intelligence Technical Debt – AITD. AITD can be harmful from both technical and social perspectives. However, developers do not know whether their systems incur AITD. Even worse, they are unaware of its sociotechnical impacts and how to mitigate them. To reduce this gap, a Systematic Literature Review – SLR was developed to uncover which types and practices of AITD exist, as well as their sociotechnical implications. Results revealed a variety of AITD types and antipatterns, as well as identification and mitigation practices. Furthermore, the findings indicate that AITD has detrimental effects on the product's quality, security, and maintainability, while also introducing challenges such as biases and discrimination. This information can support scientists and practitioners to detect and manage technical and social debt in AI-enabled software development.

Author Biographies

María Guadalupe Medina Barrera, Tecnológico Nacional de México / Instituto Tecnológico de Apizaco

Es Doctora en Planeación Estratégica y Dirección de Tecnología por la Universidad Popular Autonóma del Estado de Puebla (UPAEP). Realizó estudios de Maestría en Ciencias en Ciencias Computacionales en el Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET) y estudios de Licenciatura en Informática en el Instituto Tecnológico de Tepic, Nayarit, México. Actualmente, cuenta con el reconocimiento como candidata en el Sistema Nacional de Investigadores del CONAHCYT, además del reconocimiento al Perfil Deseable y de ser miembro del cuerpo académico “Sistemas de Información”, ambos reconocidos por PRODEP.

José Juan Hernández Mora, Tecnológico Nacional de México / Instituto Tecnológico de Apizaco

Es Doctor en Excelencia Docente  por la Universidad de los Ángeles. Tiene el grado de Maestro en Ciencias en Ciencias de la Computación en el Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), de Cuernavaca, Morelos, e Ingeniero en Computación por la Universidad Autónoma de Tlaxcala. Tiene el reconocimiento como Profesor con Perfil Deseable por parte del PRODEP, y es líder del cuerpo académico “Sistemas de Información” también reconocido por el PRODEP. También cuenta con el reconocimiento como candidato en el Sistema Nacional de Investigadores del CONAHCYT.

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How to Cite
Medina Barrera, M. G., & Hernández Mora, J. J. (2026). Technical debt in AI-enabled software development and its sociotechnical impact: A systematic literature review. Revista Colombiana De Computación, 27(1), 70–79. https://doi.org/10.29375/25392115.5072

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Published
2026-06-30
Issue
Vol. 27 No. 1 (2026): Revista Colombiana de Computación (Enero-Junio)
Section
Review article

Copyright (c) 2026 Revista Colombiana de Computación

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