Application of artificial intelligence in the prevention of corruption in public procurement: A focus on the government sector

Román-Gil C.A.; Riveros-Cuéllar A.; Carhuamaca-Cuellar M.A.; Jara-Córdova O.; Pazos-Almeyda M.A. · Multidisciplinary Reviews (2026) · DOI: 10.31893/multirev.2026559

Resumen

Corruption in public procurement weakens governance, distorts resource allocation, and erodes institutional trust. Artificial intelligence offers tools to detect irregularities through data analysis, predictive models, and automated audits. This study analyzes how AI strengthens transparency, integrity, and accountability, addressing ethical, technical, and regulatory challenges. The study adopts a qualitative approach based on a systematic literature review to analyze how artificial intelligence contributes to preventing corruption in public procurement. Clear inclusion and exclusion criteria were applied, and searches were conducted in recognized academic databases to ensure rigor, validity, and relevance in the results. The study applied the PRISMA approach to select 63 relevant articles from a total of 1,243, ensuring transparency and rigor in the systematic review. The results reveal five key trends in the use of artificial intelligence (AI) against corruption: early detection, automated auditing, predictive analytics, real-time monitoring, and assisted citizen participation. These tools enable the identification of irregularities, the anticipation of risks, and the strengthening of accountability through big data analysis and machine learning. However, their effectiveness depends on data quality, the mitigation of algorithmic biases, and model transparency. In addition, political and cultural factors influence their implementation, generating institutional resistance and contextual limitations. Overcoming these challenges requires ethical, regulatory, and participatory frameworks that integrate technological innovation with democratic governance, thus promoting the responsible and equitable use of AI to prevent and reduce corruption in public procurement. In this way, artificial intelligence strengthens transparency and control in public procurement, but requires ethical frameworks, reliable data, and institutional cooperation to overcome biases and resistance.

Instituciones: Universidad Nacional Daniel Alcides Carrión; Universidad Nacional Federico Villarreal; Universidad Nacional de Ucayali