<![CDATA[The ecosystem of higher education and scholarly publications is fundamentally based on academic integrity and ethics. However, as technology advances, this picture continues to shift significantly, especially with the advent of large language models (LLMs). The objectives of this Systematic Literature Review (SLR) are to summarize the existing research on plagiarism behavior, evaluate the efficacy of institutional rules, and consider the unique ethical issues raised by the incorporation of generative AI. The study examined 26 papers from the Scopus database that were published between 2020 and 2025 in accordance with PRISMA recommendations. The results imply that student plagiarism is mostly caused by ignorance and academic pressure. In the scientific domain, however, it appears as a complicated issue including handwriting and duplicate publications. Policies have been successful in combating classic types of plagiarism, but they have not been able to adjust to new ethical dangers. A “digital erosion of intellectual integrity” is the biggest threat posed by generative AI. Authorship and copyright concerns, as well as the failure of conventional detection technologies due to the fact that AI texts are frequently syntactically original but not conceptually original, are major obstacles. The implication is that in order to handle this technology ethically, institutions must move from a concentration on detection to a pedagogy of AI ethics, creating roadmaps and integrated decision-making frameworks.]]>
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