Artificial intelligence in government oversight: advances, challenges, and ethical perspectives from a systematic review
DOI:
https://doi.org/10.5281/zenodo.17807616Keywords:
artificial intelligence, oversight, government auditAbstract
The incorporation of Artificial Intelligence (AI) into government oversight processes represents a disruptive innovation in contemporary public management. Its application allows for the automation of tasks, the optimization of irregularity detection, and improved transparency in institutional control. However, it also poses ethical, regulatory, and organizational challenges that require systematic analysis. The objective of this research was to analyze the advances, benefits, and challenges of implementing AI in government oversight and auditing processes, identifying the main areas of application and the factors that condition its responsible adoption. A systematic qualitative-documentary review was developed following the guidelines of the PRISMA 2020 protocol. The search was conducted in the Scopus, SciELO, Redalyc, Dialnet, and Latindex databases, considering publications between 2015 and 2025. Forty-two studies that met methodological quality criteria according to the CASP (2023) instrument were selected. The findings were grouped into three thematic areas: (1) digital transformation and process automation, (2) ethical and regulatory impacts, and (3) institutional capacity building. Evidence shows that AI increases efficiency and accuracy in audits, although limitations persist due to a lack of technological infrastructure, specialized training, and robust regulatory frameworks. AI strengthens transparency, accountability, and the effectiveness of public oversight, provided it is implemented in accordance with principles of ethics, governance, and institutional training. Its responsible integration shapes a new paradigm of intelligent, predictive, and sustainable oversight.
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