AI in Education, Research and Skills Development RoundtableSummary Report
Table of contents
1 Executive Summary
2 About the Roundtable
3 Opening and high-level keynote
4 Track 1: How AI Is Transforming Education, Learning and Research
     4.1 Institution-wide AI policy and governance
     4.2 AI in Research Design, Authorship, Peer Review and Publication
     4.3 Redesigning Assessment in the Age of Generative AI
     4.4 Research Rigour, Reproducibility and Transparency
     4.5 Preventing Bias, Discrimination and Harm in AI Research
     4.6 AI-Enhanced Assessment and Automated Grading
     4.7 Open, Public AI Infrastructure for Education and Research
     4.8 AI, Inclusion and Educational Inequalities
5 Track 2: Impact of AI on Skills and Development
     5.1 Core AI Understanding for Every Graduate
     5.2 Foundational, Intermediate and Advanced AI Skills
     5.3 Distinctive Role of Universities in the AI Era
     5.4 AI Skills Suited to Microcredentials
     5.5 Lifelong Learning, Workforce Reskilling and Professional Development
     5.6 Recognition and Quality Assurance of Microcredentials
     5.7 Collaboration across Schools, Industry and International Organizations
     5.8 University Contribution Compared with Industry Training Providers
6 AI in Universities
     6.1 Personalization of Learning
     6.2 Human-AI Collaboration
     6.3 Data-Driven Education and Research
     6.4 Research and Scientific Discovery
     6.5 AI-Enhanced Research Integrity and Discovery
     6.6 Interdisciplinary Integration
     6.7 Transformation of Assessment
     6.8 Development of New Graduate Competencies
     6.9 Enhancement of Accessibility and Inclusion
     6.10 Ethical, Legal and Governance Challenges
     6.11 Addressing Bias and Harm in AI-Enabled Research
     6.12 Continuous Lifelong Learning
     6.13 Open Science and Public AI Infrastructure
     6.14 Localization and Cultural Relevance
     6.15 AI for Skills Development and Workforce Readiness
7 Summary of Discussions