La adopción de la Inteligencia Artificial en procesos de auditoría externa: barreras, desafíos y oportunidades

Abstract

The general objective of this research was to analyze the phenomenon of artificial intelligence (AI) adoption in external auditing and to identify the factors that encourage or hinder its use by accounting professionals. The study was held in Argentina between November 2024 and February 2025. A mixed-method approach was employed, using a non-experimental, descriptive, and cross-sectional research design. The main variables included the level of knowledge regarding emerging technologies, their practical implementation, and the perceived impact on audit efficiency. Data was collected through surveys and semi-structured interviews with accounting professionals from various firms across the country. The results revealed a significant gap between theoretical knowledge and practical application of AI: 96% of respondents acknowledged its importance, whereas only 14% had implemented it in their audit processes. Key barriers identified include lack of technological infrastructure, limited training, and organizational resistance to change, particularly in small and medium-sized firms. In contrast, larger firms are already utilizing these technologies for tasks such as memo production and fast analysis. Although artificial intelligence presents a concrete opportunity to improve the quality and effectiveness of external audits, it is concluded that its widespread adoption requires overcoming technological, regulatory, and cultural challenges. This study recommends developing professional training programs and regulatory frameworks that facilitate its integration across different organizational contexts.