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The rise of Artificial Intelligence (AI) in educational institutions has created many advantages in the learning environment but also raised new ethical and pedagogical concerns regarding academic integrity. This presentation investigates aspects of AI-assisted academic dishonesty on the basis of an examination of relevant university policies. Specifically examined is the extent to which policies have been developed (or not) in response to the advent of AI and, further, if and how these policies relate academic integrity to the conditions and pressures for students to engage in academic dishonesty. The underlying notion, based on sociological theories of deviance centered on anomie and strain, is that competitive pressures, academic demands and expectations, and socio-economic disparities create strains on students to engage in AI-assisted dishonesty. On the basis of an institutional policy analysis, this study explores how academic integrity policies in a sample of universities address, or fail to address, AI-assisted cheating and whether these policies create conditions that can be expected to more or less likely address conditions of strain and, hence, effectively prevent academic dishonesty in the era of AI. Findings show a wide variety of institutional responses, ranging from prohibitive academic integrity policies to a reaffirmation of principles of academic freedom and instructor autonomy, less specific policies of AI integration and, however surprisingly, an absence (as yet) of any AI-related policies in some institutions. The challenges and opportunities of AI in education are not clear at this time, but they need to be explored and clarified, an effort to which this study hopes to contribute.