Inteligencia artificial aplicada a la auditoría externa

una revisión sistemática de la literatura

Autores/as

DOI:

https://doi.org/10.37767/3008-8216(2025)001

Palabras clave:

Inteligencia artificial, Auditoría externa, Revisión sistemática, Adopción tecnológica

Resumen

Este artículo presenta una revisión sistemática de la literatura científica sobre la aplicación de la inteligencia artificial (IA) en la auditoría externa, abarcando estudios publicados entre 2010 y 2025 en revistas Q1 de auditoría, contabilidad financiera y tecnología. A partir de una búsqueda en Science Direct, Google Scholar, JSTOR y EBSCO, se identificaron 19 artículos empíricos y conceptuales que cumplen criterios de alto impacto (más de 10 citas). 
Se examinan las líneas argumentales, los marcos teóricos y metodológicos utilizados, así como debates sobre brechas de adopción entre grandes y pequeñas firmas, retos éticos y vacíos regulatorios. Finalmente, se señalan oportunidades para futuras investigaciones en áreas como interoperabilidad de tecnologías, capacitación y gobernanza de sistemas, con el fin de orientar a auditores en la integración efectiva de la IA en la práctica de auditoría externa.

Biografía del autor/a

  • Juan Ignacio Ruiz

    Contador Público (UCC), Especialista en Contabilidad y Auditoría (USiglo 21) y Magíster en Administración de Empresas (EAE Business School). Director Global de Compras y Real Estate de Apex América.  
     

Referencias

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Publicado

2026-01-29

Cómo citar

Ruiz, J. I. (2026). Inteligencia artificial aplicada a la auditoría externa: una revisión sistemática de la literatura. Revista De Estudio De Derecho Tributario, Contabilidad Y Auditoría │Universidad Blas Pascal, 3(3), 13-32. https://doi.org/10.37767/3008-8216(2025)001