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Introduction
The emergence of generative artificial intelligence (AI) has initiated one of the most significant transformations in higher education since the widespread adoption of digital learning technologies. Tools such as ChatGPT, Gemini, Copilot, and other AI-powered applications are rapidly changing how students learn, how educators teach, and how institutions design curriculum and assessment. While the initial response from many higher education institutions has centred on concerns related to academic integrity, plagiarism, and responsible use, there is increasing recognition that generative AI is no longer a peripheral technology but an integral component of contemporary educational practice.
The rapid adoption of generative AI presents both opportunities and challenges for educators, policymakers, and institutions. On one hand, AI has the potential to enhance personalised learning, provide real-time feedback, improve accessibility, support student engagement, and facilitate the development of future-focused competencies. On the other hand, concerns remain regarding overreliance on AI, ethical use, bias, transparency, assessment validity, and the potential erosion of critical thinking and problem-solving skills. These competing perspectives highlight the need to move beyond reactive responses focused solely on risk management and toward evidence-based strategies for meaningful AI integration.
Despite the growing body of research on AI in education, much of the existing literature remains focused on adoption patterns, technological capabilities, and ethical concerns. Comparatively less attention has been devoted to understanding how generative AI can be intentionally embedded into curriculum design, assessment practices, and learning environments to produce measurable educational and employability outcomes. Furthermore, there is limited empirical evidence examining the effectiveness of AI-enabled pedagogies across different disciplinary contexts and their contribution to workforce readiness in an increasingly AI-driven economy.
This Special Issue seeks to address these gaps by bringing together high-quality empirical, conceptual, and practice-oriented research on the strategic integration of generative AI in higher education. The issue aims to advance understanding of how AI can support learning effectiveness, critical thinking, student engagement, assessment innovation, and employability development while maintaining educational quality and integrity. Emphasis will be placed on studies that demonstrate measurable outcomes, offer practical implications for educators and institutions, and contribute to policy development.
Aligned with the United Nations Sustainable Development Goals, particularly SDG 4 (Quality Education) and SDG 8 (Decent Work and Economic Growth), this Special Issue provides a platform for interdisciplinary scholarship that examines the role of AI in creating inclusive, innovative, and future-ready education systems. By fostering dialogue among researchers, educators, policymakers, and industry stakeholders, the Special Issue aims to contribute to a deeper understanding of how generative AI can be leveraged to enhance educational outcomes and support sustainable workforce development in the digital age.
List of Topic Areas
Potential Topic Areas
- Strategic Integration of Generative AI in Curriculum and Assessment
- Generative AI, Learning Outcomes, and Student Success
- AI-Enabled Employability and Future Workforce Readiness
- Ethical, Responsible, and Inclusive AI in Higher Education
- Institutional Transformation and Educational Innovation
Submissions Information
Submissions are made using ScholarOne Manuscripts. Registration and access are available here: https://mc.manuscriptcentral.com/et
Author guidelines must be strictly followed. Please see here: https://www.emeraldgrouppublishing.com/journal/et
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to ““Please select the issue you are submitting to”.
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
Key Deadlines
Open submission window: 17 June 2026
Close submission window: 17 October 2026
Guest Editors
Dr. Swati Gupta, Canterbury Institute of Management, Australia, [email protected]
Prof Belinda Luke, Queensland University of Technology, Australia, [email protected]
Dr. Mayola Fernandes, Canterbury Institute of Management, Australia, [email protected]
Dr. Ruchika Rastogi, Professor, Pranveer Singh Institute of Technology, India, [email protected]
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