2026 AGUNE QM Conference in Georgia
Quality Assurance in the Digital Age: Academic Values, Learning Outcomes and Digital QA Tools
When
May 27-28, 2026
Where
University of Georgia, Tbilisi, Georgia
Agenda
Please find the conference agenda here.
Conference report
The 2026 AGUNE Quality Management Conference took place on May 27 and 28, 2026, at the University of Georgia in Tbilisi, bringing together quality management professionals, higher education representatives and international partners to discuss how digital transformation and artificial intelligence are reshaping quality assurance in higher education. Under the title “Quality Assurance in the Digital Age: Academic Values, Learning Outcomes and Digital QA Tools”, the conference addressed questions of governance, assessment, institutional quality cultures, learning outcomes and the responsible use of AI in higher education.
The conference was opened with welcome remarks by Konstantine Topuria, Rector of the University of Georgia, Ruth Rudolph cultural attaché from the German Embassy in Tbilisi, Dr. Iring Wasser, Managing Director of ASIIN, and Silvia Schmid, head of the German Academic Exchange Service’s Regional Office in Tbilisi (DAAD). Their contributions underlined the importance of international cooperation, regional academic exchange and institutional dialogue in addressing the challenges and opportunities of digital transformation in higher education. This is true both worldwide and especially in Georgia, given the current political and educational reforms.
Day 1: AI, Governance and the Future of Quality Management
The first conference day opened with a keynote by Prof. Dr. Paul Lukowicz from the German Research Center for Artificial Intelligence, who provided a broad overview of current developments in artificial intelligence and large language models. His presentation situated AI within ongoing debates on higher education and highlighted the need for universities and schools to prepare students for responsible and competent AI use. At the same time, the keynote raised important questions about how educators can ensure that AI supports deeper learning rather than replacing the acquisition of essential skills.
The regional and international dimension of academic cooperation was further addressed by Kathrin Kazimirek, DAAD Lecturer at the Business and Technology University, Georgia. She discussed the DAAD’s AI strategy in the South Caucasus, with a specific focus on German as a Foreign Language in higher education. Her contribution reflected on the outcomes of a regional workshop involving lecturers from Azerbaijan, Armenia and Georgia and discussed how AI is affecting language teaching, assessment, learner autonomy and curriculum development in the region.
In her presentation, Sophio Ugrekhelidze from the International Education Center, LEPL, Georgia, addressed the implications of AI and big data for higher education governance and quality assurance. She highlighted that quality assurance increasingly depends on the availability, interpretation and responsible use of data. The presentation drew attention to the need for stronger data literacy among institutions and policymakers, while also pointing to risks linked to poor data quality, fragmented systems and the uncritical use of AI-supported governance tools.
Prof. Dr. Mike Friedrichsen from the German University of Digital Science presented the German UDS as an example of an innovative higher education model. His contribution focused on new approaches to programme design, including stackable modules and AI-related study formats, and reflected on the broader transformation challenges faced by higher education institutions when implementing digital tools and new educational models.
The afternoon programme included an interactive session led by Irina Yefimova from the Excellent Educational Centre, Kazakhstan. The workshop invited participants to examine common challenges in internal quality assurance and programme design, using practical exercises and case-based reflection. Particular attention was given to moving beyond formal compliance with accreditation requirements towards more evidence-based and improvement-oriented quality assurance systems.
The first day concluded with a presentation by Christian Gruber from veted consulting, who discussed the shift from compliance-oriented quality assurance towards more relevant and meaningful quality management. His contribution questioned whether increasingly sophisticated quality assurance systems and performance indicators always capture what matters in academic practice. The discussion emphasised that indicators can support reflection and improvement, but should not replace institutional judgement, trust and a genuine commitment to change.
The day ended with a non-formal networking dinner, offering participants the opportunity to continue discussions in an informal setting, strengthen connections across the AGUNE network, and enjoy excellent Georgian food and traditional dance.
Day 2: Panels on Institutional Practice, AI in QA and Learning Outcomes
The second day was structured as a series of panel sessions, bringing together institutional examples, agency perspectives and practice-oriented discussions on AI, digital tools and quality enhancement. The panel format allowed participants to compare approaches across different higher education systems and to discuss how AI-related developments are already influencing quality assurance practice.
The first panel, facilitated by Prof. Revaz Tabatadze from the University of Georgia, focused on institutional approaches to AI integration in teaching, learning and quality enhancement.
Ellen Mamukelashvili from the Business and Technology University, Georgia, presented BTU’s experience with embedding AI across academic programmes. Her contribution highlighted the transition from general AI literacy towards discipline-specific AI readiness and addressed the organisational implications of integrating AI as a core element of curricula.
In the same thematic context, Nino Karkadze from Samtskhe-Javakheti State University, Georgia, presented a case study on AI-driven social CRM systems and their potential contribution to quality management and student engagement. The presentation showed how digitally supported communication and feedback mechanisms can strengthen continuous improvement processes, particularly in regional higher education institutions seeking to align internal quality assurance with international expectations.
Hameed Sulaiman from Sultan Qaboos University, Oman, presented an approach to link learning outcomes, employability and sustainability competencies through student portfolios. His presentation highlighted the role of students as end-beneficiaries of quality assurance and showed how portfolios and competency mapping can help students better understand and communicate their learning achievements in relation to broader frameworks such as the UN Sustainable Development Goals.
Ketevan Givishvili from the University of Georgia presented institutional examples of digitalisation and AI-supported quality enhancement. Her contribution illustrated how data-informed decision-making and digital tools can support institutional improvement, strengthen internal processes and contribute to the development of a stronger quality culture.
The discussion following the first panel reflected the diversity of institutional approaches presented and underlined how AI is already being applied in different areas of higher education practice. Participants particularly addressed questions of assessment validity, academic integrity and the extent to which student work can still be clearly identified as students’ own in AI-supported learning environments. The discussion also raised broader questions about skills and competencies, including how institutions can foster not only technical AI literacy but also normative competencies such as critical judgement, responsibility and ethical reflection. In this context, participants reflected on the purpose of AI modules in curricula: whether they should primarily introduce students to the use of AI tools, support discipline-specific professional readiness, or contribute to a broader transformation of teaching and learning. Cooperation emerged as a key theme as participants emphasised the need to exchange practical experiences, develop shared understandings and learn from different institutional applications of AI and digital tools.
The second panel addressed AI in agency work, facilitated by Lasha Macharashvili from Alte University, Georgia. This session shifted the focus from institutional implementation to external quality assurance and accreditation practice.
Within this panel, Lali Odishvili from the National Center for Educational Quality Enhancement, Georgia, presented current reflections on incorporating AI tools into external quality assurance procedures. Her contribution considered possible applications such as document analysis, benchmarking and evaluation support, while stressing the need for ethical principles, transparency, data protection, inclusivity and continued human oversight in peer review-based processes.
Julia Tohidi Sardasht from ASIIN, Germany, contributed an agency perspective on assessing AI in accreditation procedures. Her input explored how AI is increasingly becoming relevant to the everyday work of programme accreditation, including questions of learning outcomes, curriculum design, assessment, academic integrity and internal quality assurance. Rather than treating AI as a separate technical issue, the presentation emphasised how existing quality assurance principles can guide agencies and expert panels in asking appropriate questions in a changing higher education landscape.
The agency panel prompted a discussion on the role of AI in external quality assurance and accreditation practice. One central question concerned whether accreditation is increasingly perceived as a burden by higher education institutions and whether AI could help reduce administrative workload, for example by supporting document preparation, analysis or evidence management. At the same time, participants raised the challenge of assessing the real impact of AI in higher education, as opposed to merely reviewing what is stated in institutional documents, policies or regulations. This was discussed as a fundamental limitation and continuing challenge of quality assurance: the need to distinguish between formal claims and actual implementation. Against this background, the importance of capacity building within quality assurance agencies was stressed, particularly with regard to staff expertise, methodological competence and the responsible use of AI-supported tools. The discussion also highlighted the continuing value of on-site visits as a “reality check”, allowing expert panels to verify how AI-related strategies and quality assurance measures are understood, implemented and experienced in practice.
The conference concluded with a wrap-up session that brought together the central themes of the two days before the conference attendees took part in a guided city tour, discovering the old town of Tbilisi.
Key Themes and Outlook
Across the two conference days, several key themes emerged. First, AI is already influencing higher education at multiple levels: from teaching and learning to curriculum design, student engagement, institutional governance and external accreditation. Second, the use of AI and digital tools places renewed emphasis on data quality, transparency, ethical decision-making and institutional capacity. Third, the discussions showed that digital transformation should not be understood primarily as a technical process, but as a strategic and values-based challenge for higher education institutions and quality assurance bodies.
The conference also demonstrated the importance of international and regional networks such as AGUNE in supporting peer exchange on emerging topics. By bringing together institutional leaders, quality assurance professionals, agency representatives and international partners, the event created a valuable forum for sharing experiences and identifying common challenges in the digital transformation of quality assurance.
