By July 2026, the use of generative neural networks in Russian higher education has crossed the threshold of a marginal phenomenon to become a systemic reality. Statistics recorded in the second quarter of this year demonstrate that one-third of all checked student papers contain signs of algorithmic participation. This indicates not so much a crisis of academic integrity as a fundamental shift in approaches to content generation. Technologies have ceased to be an external tool and have integrated into the learning process itself, changing the nature of student assignments.
The profile of leading majors presents particular interest. While the presence of AI in humanities disciplines, such as Art History and Media, is explained by the nature of text-based tasks, high indicators in Computer and Information Sciences indicate the professionalization of tool usage. For students at technical universities, neural networks have already become a standard assistant, analogous to a calculator, rather than a means of bypassing the system. This creates a challenge for employers expecting graduates to possess skills distinct from simple prompting.
The market’s response regarding monitoring confirms this trend. The system being developed by Antiplagiat is shifting focus from binary plagiarism detection to detailing the nature of fragment usage. This signifies a transition from fighting plagiarism to verifying the author's intellectual contribution. Under conditions where AI becomes a basic tool, educational institutions will have to revise assessment criteria, emphasizing not the quality of the final text, but the ability to formulate tasks and critically analyze generated solutions.