The Impact of Artificial Intelligence on Academic Space: Integrity, Inequality, and Interdisciplinary Transformation

Abstract

The rapid development of generative artificial intelligence, particularly ChatGPT and similar language models, has led to significant changes in academic environments. These technologies transform teaching and learning practices, revolutionizing the entire academic ecosystem. Over the past two years, the dramatic increase in AI accessibility has forced higher education institutions to face unprecedented adaptation challenges. By 2024, 83% of higher education institutions globally will have revised their policies in response to AI technologies. In developing countries like Georgia, AI integration is particularly complex due to existing structural challenges—limited resources, unequal digital access, and inconsistent educational policies. Nevertheless, AI adaptation presents a unique opportunity to overcome traditional barriers and create innovative models for education and research. Research Aim and Objectives This study examines the impact of artificial intelligence on Georgia's higher education system, focusing on three interconnected aspects: Academic Integrity - how AI changes traditional understanding of plagiarism, authorship, and intellectual labour, and how institutions should adapt to maintain ethical standards; Digital Inequality - how unequal access to AI technologies affects existing social and institutional inequalities, and what strategies can reduce this inequality; Interdisciplinary Transformation - how AI facilitates crossing disciplinary boundaries and creates new collaborative models. The specific objectives are: To analyze current practices and attitudes regarding AI usage among academic staff and students; To identify patterns of AI access inequality across demographic groups and disciplines; To assess AI's impact on interdisciplinary collaboration; To analyze existing institutional policies related to AI; To develop evidence-based recommendations for institutional policy. Methodology The study employs a mixed methods approach. The quantitative component included an online survey with 173 respondents (92 students and 81 academic staff) from various disciplines. The questionnaire consisted of 35 closed-ended and seven open-ended questions assessing AI usage practices, attitudes, barriers, and opportunities. The qualitative component consisted of nine semi-structured interviews with university leadership, faculty deans, and program directors, focusing on institutional challenges and strategies related to the integration of AI. To ensure data diversity, the study involved seven higher education institutions, four of which are located in the capital city and three in different regions. Respondent selection used stratified sampling to ensure representation from various disciplines, social groups, and institutional types. Key Findings Academic Integrity: 78% of academic staff report significant changes in teaching methods since AI emergence. 82% of students use AI for academic purposes, but only 31% disclose this to instructors. 67% believe existing plagiarism policies inadequately address AI challenges; Most universities lack clearly articulated policies regarding the use of AI. 45% of academic staff lack sufficient training to understand ethical aspects of AI usage. Digital Inequality: Representatives of humanities disciplines use AI tools 43% less frequently than those in STEM fields; Regional university students use AI 37% less than capital university students; Low socioeconomic status students use premium AI services 52% less frequently; 57% of academic staff and 63% of students identify language barriers as hindrances to effective AI usage. Interdisciplinary Transformation: 43% increase in interdisciplinary collaboration directly linked to AI use; 64% of academic staff note that AI tools help them understand concepts from other disciplines; Interdisciplinary projects increased from 25 (2022) to 43 (2024), representing 72% growth; Seventy-one per cent of students believe that AI promotes interdisciplinary thinking and problem-solving abilities. Recommendations and Significance Based on research findings, the paper presents ethical guidelines and policy recommendations aimed at maximizing the academic benefits of AI while minimizing risks: Developing clear policies for AI usage that consider both disciplinary and institutional contexts; Creating AI literacy programs for students and staff, with a focus on regional universities and humanities; Implementing innovative assessment methods focused on critical thinking and creativity; Developing strategies to reduce digital inequality, including expanding technology access and supporting native-language AI tools; Promoting interdisciplinary programs and projects using AI to transcend disciplinary boundaries. The study emphasises the critical importance of digital transformation in Georgia's higher education and provides a foundation for effective AI integration in academic environments. The results are relevant not only for Georgia but also for other developing countries facing similar technological adaptation challenges.