Author
Listed:
- Darren Yi Sern Low
- Kar Ming Shaw
- Poovarasi Balan
Abstract
Artificial intelligence (AI) and big data have revolutionized various industries, including education, by improving efficiency and decision‐making. Within higher education institutions (HEIs), these technologies hold immense potential in advancing sustainable development (SD) aligned with the United Nations' Sustainable Development Goals (SDGs). This paper aims to examine the integration of SD in HEIs through the lens of AI and big data, identifying key challenges and highlighting opportunities for effective action from four institutional dimensions, namely technological, organizational, social and environmental. The methodology is based on bibliometric analyses and screening of relevant studies to identify connections on the integration of AI in HEIs toward SD, as well as exemplifying studies in building the foundation of discussions on the challenges and proposed solutions in this integration. Findings from bibliometric analyses, screening and review of literature show that despite the promising benefits and upward trend, integrating SD with AI and big data within HEIs remains complex, spanning across technological, organizational, social, and environmental dimensions. Addressing these multifaceted hurdles necessitates coordinated efforts and among educators, policymakers, and industries to align innovation with sustainability. This paper pinpoints critical obstacles and delivers strategic recommendations to facilitate the seamless adoption of AI‐driven sustainability practices in HEIs. It underscores the transformative potential of AI and big data to reshape institutional operations, drive systemic change, and foster long‐term positive outcomes in education.
Suggested Citation
Darren Yi Sern Low & Kar Ming Shaw & Poovarasi Balan, 2026.
"Sustainable Development Integration in Higher Education Institutions: Challenges and Opportunities in the Age of AI and Big Data,"
Sustainable Development, John Wiley & Sons, Ltd., vol. 34(2), pages 2386-2408, April.
Handle:
RePEc:wly:sustdv:v:34:y:2026:i:2:p:2386-2408
DOI: 10.1002/sd.70446
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