Inteligencia artificial en los sistemas de información contable: desafíos y oportunidades para la auditoría interna

Contemporary organizations face growing demands for traceability, timeliness, and reliability in their financial information, in an environment where traditional Accounting Information Systems (AIS) show structural limitations in processing increasingly heterogeneous data volumes and in sustaining effective internal control schemes. This theoretical and documentary article analyzes the potential of Artificial Intelligence (AI) to optimize AIS and strengthen internal auditing as a control mechanism for financial information quality. Through a systematic review of scientific literature published between 2021 and 2026 in indexed databases (Scopus, Web of Science, ScienceDirect, Springer, Emerald, MDPI), the main findings on continuous auditing, machine learning, process mining, and blockchain applied to accounting are synthesized. As a result, an integrative conceptual model, the IASIC Model, is proposed, articulating technological, control, data governance, and financial information quality components, of general application to organizations across economic sectors. It is concluded that AI integration into AIS is a necessary, though not sufficient, condition for improving financial information quality.