Volume 4, 2026 – Issue 1 
AI, IoT, and the evolution of learning processes: A systematic review using a PESTEL perspective
Khaoula Mahfoud
1 *, and Aziz Bensbahou
2
Faculty of Economics and Management, Ibn Tofaïl University, Kenitra, Morocco
Corresponding author: khaoula.mahfoud@uit.ac.ma
DOI: 10.5281/zenodo.18840980
Abstract
The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) into education is reshaping learning by creating more adaptive, interactive, and learner-centered environments. This study examines how these technologies influence education through the PESTEL framework, highlighting the political, economic, social, technological, environmental, and legal factors that shape their adoption. In fact, the choice of the PESTEL framework is based on its capacity to build a comprehensive macro-environmental analysis of the educational landscape. And using the PRISMA approach (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), the methodology includes a systematic identification of relevant studies, textual analysis of co-occurrences and author collaborations, and content analysis based on a structured analytical grid. The results indicate that political factors—such as government policies, national digital strategies, and public–private partnerships—play a pivotal role in enabling or constraining the implementation of AI and IoT in education. Economic considerations, social equity issues, technological readiness, environmental implications, and legal regulations also emerge as significant drivers. Overall, this review provides a comprehensive understanding of the multi-dimensional impact of AI and IoT on education and underscores the need for informed, forward-looking policies to support their responsible and effective integration.
Keywords: AI, IoT, learning, PESTEL, SLR
Published
2026/02/28
—
Section
Research Papers
How to Cite (APA)
Download Citation: EndNote/Zotero/Mendeley (RIS)
References
Alaeifar, P., Pal, S., Jadidi, Z., Hussain, M., & Foo, E. (2024). Current approaches and future directions for Cyber Threat Intelligence sharing: A survey. Journal of Information Security and Applications, 83, 103786. ScienceDirect. https://doi.org/10.1016/j.jisa.2024.103786
Chatterjee, S., Chaudhuri, R., Mariani, M., & Fosso Wamba, S. (2023). Examining the role of intellectual capital on knowledge sharing in digital platform-based MNEs and its impact on firm performance. Technological Forecasting and Social Change, 197, 122909. ScienceDirect. https://doi.org/10.1016/j.techfore.2023.122909
Deighton, K., Kuys, B., & Tyagi, S. (2024). Industrial Design education in Australia: A competence analysis across primary, secondary and tertiary education levels. International Journal of Technology and Design Education, 34(1), 427–460. Springer. https://doi.org/10.1007/s10798-023-09822-0
Fang, F., & Jiang, X. (2024). The Analysis of Artificial Intelligence Digital Technology in Art Education under the Internet of Things. IEEE Access, 12, 22928–22937. WOS. https://doi.org/10.1109/ACCESS.2024.3363655
Kim, B.-J., Kim, M.-J., & Lee, J. (2024). Code green: Ethical leadership’s role in reconciling AI-induced job insecurity with pro-environmental behavior in the digital workplace. Humanities and Social Sciences Communications, 11(1), 1627. Springer. https://doi.org/10.1057/s41599-024-04139-2
Kruger, S., & Steyn, A. A. (2024). Developing breakthrough innovation capabilities in university ecosystems: A case study from South Africa. Technological Forecasting and Social Change, 198, 123002. ScienceDirect. https://doi.org/10.1016/j.techfore.2023.123002
Lai, J., Gan, W., Wu, J., Qi, Z., & Yu, P. S. (2024). Large language models in law: A survey. AI Open, 5, 181–196. ScienceDirect. https://doi.org/10.1016/j.aiopen.2024.09.002
Mendonça, S., Damásio, B., Charlita de Freitas, L., Oliveira, L., Cichy, M., & Nicita, A. (2022). The rise of 5G technologies and systems: A quantitative analysis of knowledge production. Innovation in 5G Technology: Leadership, Competition and Policy Issues., 46(4), 102327. ScienceDirect. https://doi.org/10.1016/j.telpol.2022.102327
Qiu, Y., Isusi-Fagoaga, R., & García-Aracil, A. (2023). Perceptions and use of metaverse in higher education: A descriptive study in China and Spain. Computers and Education: Artificial Intelligence, 5, 100185. ScienceDirect. https://doi.org/10.1016/j.caeai.2023.100185
Saba, C. S., & Monkam, N. (2025). Artificial intelligence’s (AI’s) role in enhancing tax revenue, institutional quality, and economic growth in selected BRICS-plus countries. Journal of Social and Economic Development. Springer. https://doi.org/10.1007/s40847-024-00401-0
Sanusi, I. T., Olaleye, S. A., Agbo, F. J., & Chiu, T. K. F. (2022). The role of learners’ competencies in artificial intelligence education. Computers and Education: Artificial Intelligence, 3, 100098. ScienceDirect. https://doi.org/10.1016/j.caeai.2022.100098
Zhang, J., & Song, X. (2024). The AI-assisted Traditional Design Methods for the Construction Sustainability: A Case Study of the Lisu Ethnic Minority Village. Natural and Engineering Sciences, 9(2), 213–233. Scopus. https://doi.org/10.28978/nesciences.1569562
About the authors
- Khaoula Mahfoud is a PhD student at Ibn Tofail University and the Head of Inter-Organizational Research Coordination Service at the Ministry of Higher Education, Scientific Research and Innovation, Morocco.
khaoula.mahfoud@uit.ac.ma
↩︎ - Aziz Bensbahou is a professor (PES) at Ibn Tofail University in Kenitra, Morocco. He is a member of the Economics and Public Policy Research Laboratory (LSEPP) and serves as coordinator of the Research Master’s program in Economics, Public Policies, and Development (MEPPD). He is a member of the editorial board of the Revue Repères et Perspectives Économiques (RRPE) and is also a member of the Moroccan Center for Research and Policy Analysis (CEMRAP).
bensbahou.aziz@uit.ac.ma
↩︎


