Academic integrity in the age of artificial intelligence: challenges, risks and opportunities for latin american universities
Keywords:
Academic integrity, generative artificial intelligence, higher education, assessment, university governanceAbstract
The expansion of generative artificial intelligence has shifted academic integrity from a discussion centered on plagiarism and authorship toward an institutional challenge involving learning, assessment, transparency, and governance. The objective of this article was to analyze the challenges, risks, and opportunities that generative artificial intelligence poses to Latin American universities and to propose an operational framework for responsible use policies. A documentary review was conducted using a Scopus file exported on August 3, 2026, initially comprising 51 records. Based on criteria of recency, thematic relevance, higher education focus, and availability of a digital object identifier, exactly 20 articles published between 2025 and 2026 were selected. The analysis was organized into six dimensions: adoption and dependence, authorship and disclosure of use, authentic assessment, reliability of detection tools, artificial intelligence literacy, and institutional governance. The evidence shows that university responses cannot be limited to prohibitions or automated detection systems. Recent studies describe the rapid normalization of generative artificial intelligence, differences between faculty and students, regulatory ambiguity, equity concerns, and risks of cognitive delegation. At the same time, opportunities were identified for feedback, self-regulated learning, assessment redesign, and traceable human and artificial intelligence coauthorship. An academic integrity model is proposed based on proportional disclosure, evidence of the work process, content verification, assessment redesign, and institutional literacy.
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