New rules for using AI in universities: what is changing for lecturers and students

6 Липня 2026

Students have long been using ChatGPT and other AI tools for learning. As a result, universities are now starting to define clear rules that determine where the use of technology ends and where violations of academic integrity begin.

Following updates to academic integrity requirements, higher education institutions can no longer rely on general recommendations. They need to define clear rules for the use of artificial intelligence and adapt their approaches to student assessment.

“Universities today do not need new bans, but new rules for working with technology. Our task is to help educational institutions go through this transition quickly, confidently, and based on the best international practices. That is why we bring together education, government, and the tech community to create solutions that can be implemented today,” says Olha Shapoval, Executive Director of Kharkiv IT Cluster.

To address this need, Kharkiv IT Cluster held a three-day workshop “Academic Integrity and AI: How to Develop an Institutional Policy in Line with New Legislative Requirements.” The initiative was partnered by the National Agency for Higher Education Quality Assurance, with Ukraine Global Faculty serving as the international hosting platform.

The discussion brought together representatives of the Verkhovna Rada of Ukraine, the Ministry of Digital Transformation of Ukraine, the international company StrikePlagiarism, and Ukrainian universities.

The workshop united 1,895 participants from more than 150 higher education institutions across Ukraine.

What you need to know about academic integrity in the age of AI

• Universities are moving from bans to disclosure of AI use

The use of artificial intelligence is not considered a violation of academic integrity. Instead, more and more institutions are adopting a transparency-based model. Students are expected to indicate which AI tools they used, for which tasks (idea generation, structuring, editing, or translation), and what part of the work they completed independently.

• AI detectors are no longer sufficient proof of misconduct

Modern AI detection tools cannot automatically confirm academic dishonesty. A high probability score does not necessarily mean a student has violated the rules. These tools can be inaccurate, especially when AI is used for translation, formatting, or information search. Therefore, detector results should be treated only as a signal for further review, not as final evidence.

• If AI can complete the assignment, the assignment itself should be reconsidered

If students can fully complete a task using AI, the issue lies not only in technology use but also in the task design. Universities are encouraged to use more oral defenses, project-based work, draft analysis, and practical case studies that better assess students’ actual competencies.

• AI policies should be integrated into course descriptions

Students need to clearly understand AI usage rules within each discipline and specific assignment. Therefore, AI policies should be embedded into course syllabi rather than exist as separate institutional documents.

• Transparency should apply equally to students and lecturers

If lecturers use artificial intelligence to prepare teaching materials, design tests, or provide feedback, they should also disclose this to students. The rules should apply equally to all participants in the educational process.

After the workshop, participants received a step-by-step framework for developing institutional AI policies, internal document templates, practical recommendations for integrating AI into education, and tools for updating assessment systems.

To help educators navigate changes related to the use of artificial intelligence, Kharkiv IT Cluster is developing an open community of lecturers interested in AI. The community already brings together more than 2,000 members from universities across Ukraine.

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Workshop materials