The rapid advancement of Artificial Intelligence (AI) is profoundly reshaping higher education, research practices, and innovation ecosystems worldwide. While AI offers significant opportunities to enhance knowledge production, learning personalisation, and research efficiency, its uncritical adoption risks reinforcing technocratic, inequitable, and ethically fragile educational models. This paper argues that current higher education responses to AI remain overly focused on technological capability and efficiency, with insufficient attention to learner agency, ethical judgement, sustainability, and social responsibility. Drawing on heutagogy (self-determined learning) as a central pedagogical framework, the paper proposes a repositioning of research, innovation, and sustainable education in the age of AI.

Using a critical and integrative conceptual approach, the paper synthesises literature across education for sustainable development (ESD), AI ethics, higher education pedagogy, and innovation studies to demonstrate how heutagogy operationalises responsible and human-centred engagement with AI. The analysis highlights how heutagogical principles, learner autonomy, reflexivity, capability development, and lifelong learning, enable individuals and institutions to move beyond information acquisition towards informed decision-making and responsible action. The paper further examines the implications of heutagogy for AI-enabled research and innovation, emphasising research integrity, ethical governance, interdisciplinary inquiry, and societal relevance.

Importantly, the paper situates this discussion within Global South and Pacific Island contexts, where digital divides, cultural knowledge systems, and sustainability vulnerabilities necessitate contextually grounded and decolonising educational approaches. It argues that heutagogy provides a powerful mechanism for integrating indigenous and local knowledge with global AI technologies while safeguarding cultural identity and community wellbeing. The paper concludes by outlining strategic policy and practice implications for universities, positioning heutagogy as a critical enabler of ethical AI adoption, sustainable innovation, and future-ready higher education systems. In doing so, it contributes a timely conceptual framework for aligning Artificial Intelligence with human values, sustainability imperatives, and the public good.

Heutagogy, Artificial Intelligence, Sustainable Education, Research and Innovation, Education for Sustainable Development, AI Ethics, Higher Education, Human Agency, Pacific and Global South Contexts

1. Blaschke, L. M. (2012). Heutagogy and lifelong learning: A review of heutagogical practice and self-determined learning.

2. Blaschke, L. M., & Hase, S. (2019). Heutagogy and digital media networks: Setting students on the path to lifelong learning. Pacific Journal of Technology Enhanced Learning, 1(1), 1–14. https://doi.org/10.24135/pjtel.v1i1.1

3. Blaschke, L. (2021). Heutagogy: The pedagogy of agency. Pacific Journal of Technology Enhanced Learning, 3(1), 45. https://doi.org/10.24135/pjtel.v3i1.110

4. Hase, S., & Kenyon, C. (2007). Heutagogy: A child of complexity theory. Complicity: An International Journal of Complexity and Education, 4(1), 111–118.

5. Matthews, J. (2024). From traditional to transformed: Leveraging AI to craft adaptive, interconnected educational landscapes. Pacific Journal of Technology Enhanced Learning, 6(1), 8–9. https://doi.org/10.24135/pjtel.v6i1.180

6. Nabou, S. S. (2024). An Indigenous Fijian perspective: Prioritising Indigenous Fijian values and aspirations in decolonising early childhood education. Rangahau Aranga: AUT Graduate Review, 3(1). https://doi.org/10.24135/rangahau aranga.v3i1.219

7. Narayan, V., & Vanderburg, R. (2025). Heutagogy and Gen AI: A conversation. Pacific Journal of Technology Enhanced Learning, 7(2), 50. https://doi.org/10.24135/pjtel.v7i2.238

8. Newfield, T. (2025). Heutagogy in education: Fostering self directed learning for the 21st century. Journal of Career and Technical Education, 40(1), Article 500. https://doi.org/10.21061/jcte.500

9. Puloka Luey, E. C., Manning, R., & Ratuva, S. (2024). The status of Indigenous knowledge, environmental issues and climate change in science education: Talanoa from Tonga and Vanuatu secondary schools. University of Canterbury Research Archive. http://doi.org/10.26021/15181

10. Santos, B. de S. (2018). The end of the cognitive empire: The coming of age of epistemologies of the South. Duke University Press.

11. Selwyn, N. (2019). Should robots replace teachers? AI and the future of education. Polity Press.

12. Smith, L. T. (2012). Decolonizing methodologies: Research and Indigenous peoples (2nd ed.). Zed Books.

13. Sterling, S. (2010). Learning for resilience, or the resilient learner? Towards a necessary reconciliation in a paradigm of sustainable education. Environmental Education Research, 16(5–6), 511–528. https://doi.org/10.1080/13504622.2010.505427

14. UNESCO. (2017). Education for sustainable development goals: Learning objectives. UNESCO Publishing.

15. UNESCO. (2022). Recommendation on the ethics of artificial intelligence. UNESCO Publishing. https://unesdoc.unesco.org/ark:/48223/pf0000381137

16. UNESCO. (2025). Regional collaboration strengthens education in Pacific Island countries. UNESCO. https://www.unesco.org/en/articles/regional collaboration strengthens education pacific island countries

17. University of the South Pacific, Institute of Education. (2024). A step forward in integrating indigenous knowledge in mainstream education. USP. https://www.usp.ac.fj/institute of education/news/a step forward in integrating indigenous knowledge in mainstream education/

18. Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1798995