Artificial Intelligence as a Compounding Enabler in the Implementation of Green Energy Technology Policies in South Africa
DOI:
https://doi.org/10.65582/gti.2026.016Keywords:
Artificial Intelligence, Green Energy Technology, South Africa, Just Energy Transition (JET), Algorithmic Governance, 4th Industrial Revolution (4IR)Abstract
This paper examines how Artificial Intelligence (AI) functions as a compounding factor to support the execution of green energy technology policies within South Africa. We contend that artificial intelligence has shifted from a peripheral technological resource to a mechanical imperative for policy effectiveness, capable of magnifying current institutional strengths to surmount deep-seated bureaucratic and technical obstacles that hinder the move from policy design to operational execution. The study applies a rigorous qualitative methodology centered on comprehensive desktop literature review and document analysis, examining a curated corpus of national policy documents, legislative frameworks, municipal reports, and peer-reviewed journal articles. Our theoretical framework draws on policy implementation literature and complexity governance models describing policy systems as adaptive, non-linear, and path dependent. The results indicate three primary conceptual findings. Initially, AI acted as a critical instrument for grid stabilization by predictive dispatch and real-time load balancing; empirical evidence indicates that AI-powered energy management can raise renewable capacity per unit of adoption by as much as 42.8 percent. Secondly, AI strengthens municipal fiscal sustainability by automating energy audits and reducing revenue leakage, while also reinforcing monitoring and compliance via real-time tracking of environmental sustainability metrics. Third, AI supports a socially equitable Just Transition by applying machine learning to energy poverty mapping and labor skill-alignment. Furthermore, we recognize that artificial intelligence functions as an essential instrument for reconciling historical fragmentation in South Africa’s energy governance, establishing a shared structural foundation that supports smooth inter-agency coordination. Nevertheless, the results highlight major structural limitations, namely a severe digital infrastructure gap, acute technical skills shortages within the public sector, and the risk of an AI accountability vacuum.
References
Ahmad, T., Zhu, H., Zhang, D., Tariq, R., Bassam, A., Ullah, F., AlGhamdi, A.S. and Alshamrani, S.S. 2022. Energetics systems and artificial intelligence: Applications of industry 4.0. Energy Reports, 8, pp. 334–361. DOI: doi.org/10.1016/j.egyr.2021.11.256
Ajayi, F., Ademola, O.M., Amuda, K.F. and Alade, B. 2024. AI-driven decarbonization of buildings: Leveraging predictive analytics and automation for sustainable energy management. World Journal of Advanced Research and Reviews, 24(1), pp. 061–079. DOI: doi.org/10.30574/wjarr.2024.24.1.2997
Almeida, P.G.R. de and Santos Júnior, C.D. dos. 2025. Artificial intelligence governance: Understanding how public organizations implement it. Government Information Quarterly, 42(1), article 102003. DOI: doi.org/10.1016/j.giq.2024.102003
Apata, O., Munda, J.L. and Migabo, E.M. 2026. Artificial intelligence for predictive maintenance and performance optimization in renewable energy systems: A comprehensive review. Energies, 19(2), article 536. DOI: doi.org/10.3390/en19020536
Balamurugan, M., Narayanan, K., Raghu, N., Arjun Kumar, G.B. and Trupti, V.N. 2025. Role of artificial intelligence in smart grid – a mini review. Frontiers in Artificial Intelligence, 8, article 1551661. DOI: doi.org/10.3389/frai.2025.1551661
Baloyi, W.M., Meyer, N. and Rossouw, D. 2025. A critical review of the enablers and constraints of artificial intelligence in the South African public sector. Journal of Contemporary Management, 22(1), pp. 380–403. Available at: https://journals.co.za/journal/jcman [Accessed 1 May 2026].
Bawa, S. 2025. Leveraging artificial intelligence and dynamic supply chains for renewable energy development in Africa’s frontier markets. Energy & Environment (advance online publication). DOI: doi.org/10.1177/0958305X251375931
Bowman, A. 2020. Parastatals and economic transformation in South Africa: The political economy of the Eskom crisis. African Affairs, 119(476), pp. 395–431. DOI: doi.org/10.1093/afraf/adaa013
Chen, C.-f., Yao, B., Kar, B., Hu, Y. and Napolitano, R. 2024. Addressing machine learning bias to foster energy justice. Energy Research & Social Science, 108, article 103392. DOI: doi.org/10.1016/j.erss.2024.103392
Chilenga Butao, T. 2024. Slowing down a moving train: the DMRE’s response to South Africa’s just energy transition. Policy Brief. Johannesburg: Public Affairs Research Institute. Available at: https://pari.org.za/wp-content/uploads/2024/12/20241211_DMREPolicyBrief_ChilengButao.pdf [Accessed 20 June 2026].
Cowls, J., Tsamados, A., Taddeo, M. and Floridi, L. 2023. The AI gambit: Leveraging artificial intelligence to combat climate change – opportunities, challenges, and recommendations. AI & Society, 38(1), pp. 283–307. DOI: doi.org/10.1007/s00146-021-01294-x
Das, D. 2025. Integrating IoT and AI for sustainable energy-efficient smart building: Potential, barriers and strategic pathways. Sustainability, 17(22), article 10313. DOI: doi.org/10.3390/su172210313
Shumba, T., Radebe, H., Dippenaar, J., Euston-Brown, M. and Africa, S.E., 2019. The Impact of Small Scale Embedded Generation on Municipal Revenue. In Conference Paper, 27th AMEU Technical Convention. Available at: https://www.cityenergy.org.za/wp-content/uploads/2021/02/resource_500.pdf [Accessed 16 June 2026].
Donkoh, S. and Mensah, J. 2023. Application of triangulation in qualitative research. Journal of Applied Biotechnology and Bioengineering, 10(1), pp. 6–9. DOI: doi.org/10.15406/jabb.2023.10.00319
Eberhard, A. and Naude, R. 2016. The South African Renewable Energy Independent Power Producer Procurement Programme: A review and lessons learned. Journal of Energy in Southern Africa, 27(4), pp. 1–14. DOI: doi.org/10.17159/2413-3051/2016/v27i4a1483
Effoduh, J.O. 2024. Africa’s energy poverty in an artificial intelligence (AI) world: Struggle for sustainable development goal 7. Journal of Sustainable Development Law and Policy, 15(3), pp. 32–63. DOI: doi.org/10.4314/jsdlp.v15i3.2
Egbuna, I.K., Salihu, F.B., Okara, C.C., Olayiwola, D.E., Smart, E.E., Anifowose, O. and Mbamalu, P.O. 2025. Advances in AI-powered energy management systems for renewable-integrated smart grids. World Journal of Advanced Engineering Technology and Sciences, 15(2), pp. 2300–2325. DOI: doi.org/10.30574/wjaets.2025.15.2.0685
Elmore, R.F. 1985. Forward and backward mapping: Reversible logic in the analysis of public policy. In: K. Hanf and T.A.J. Toonen, eds. Policy Implementation in Federal and Unitary Systems. Dordrecht: Martinus Nijhoff, pp. 33–70. DOI: doi.org/10.1007/978-94-009-5089-4_4
Folly, K. 2021. Competition and restructuring of the South African electricity market. In: T. Pinto, Z. Vale and S. Widergren, eds. Local Electricity Markets. London: Academic Press, pp. 315–338. DOI: doi.org/10.1016/B978-0-12-820074-2.00002-2
Fose, N., Singh, A.R., Krishnamurthy, S., Ratshitanga, M. and Moodley, P. 2024. Empowering distribution system operators: A review of distributed energy resource forecasting techniques. Heliyon, 10(15), article e34800. DOI: doi.org/10.1016/j.heliyon.2024.e34800
Hjern, B. and Porter, D.O. 1981. Implementation structures: A new unit of administrative analysis. Organization Studies, 2(3), pp. 211–227. DOI: doi.org/10.1177/017084068100200301
Jalonen, H. 2025. A complexity theory perspective on politico-administrative systems: Insights from a systematic literature review. International Public Management Journal, 28(1), pp. 1–21. DOI: doi.org/10.1080/10967494.2024.2333382
Kambule, N., Yessoufou, K. and Nwulu, N. 2022. Formulating best practice recommendations for prepaid electricity meter deployment in Soweto, South Africa – Capitalising on the developed-world’s experiences. Journal of Public Affairs, 22(4), article e2646. DOI: doi.org/10.1002/pa.2646
Kampira, A. and Mukonza, R.M. 2025. E-government/AI integration state and capacity in developing countries: A systematic review. Administrative Sciences, 15(12), article 482. DOI: doi.org/10.3390/admsci15120482
Khoza, H.H. and Mukonza, R.M. 2025. Load-shedding crises and its effects on digitalization in South Africa post-COVID-19. International Journal of Research in Business and Social Science, 14(6), pp. 422–434. DOI: doi.org/10.20525/ijrbs.v14i6.3867
Koumoulos, P.P., Mazarakis, L., Katsoulis, S., Zantalis, F. and Koulouras, G. 2026. IoT and AI-driven approaches for energy optimization in off-grid solar systems. Engineering Proceedings, 124(1), article 67. DOI: doi.org/10.3390/engproc2026124067
Kozonogova, E. and Dubrovskaya, J. 2022. Assessing the convergence of the digital infrastructure development in the RF regions: Spatial analysis. In: T. Antipova, ed. Comprehensible Science. ICCS 2021. Lecture Notes in Networks and Systems, Vol. 315. Cham: Springer, pp. 118–129. DOI: doi.org/10.1007/978-3-030-85799-8_11
Kumar, B.R. 2025. Sustainable finance in different industry sectors. In: Green Finance (Sustainable Finance series). Cham: Springer. DOI: doi.org/10.1007/978-3-032-03333-8_8
Lawrence, A. 2020. Energy decentralization in South Africa: Why past failure points to future success. Renewable and Sustainable Energy Reviews, 120, article 109659. DOI: doi.org/10.1016/j.rser.2019.109659
Li, J., Wang, C. and Liu, Y. 2026. AI-driven virtual power plants: A comprehensive review. Energies, 19(4), article 1084. DOI: doi.org/10.3390/en19041084
Lipsky, M. 1980. Street-level bureaucracy: Dilemmas of the individual in public services. New York: Russell Sage Foundation. https://doi.org/10.1177/003232928001000113
Mack, N., Woodsong, C., MacQueen, K., Guest, G. and Namey, E. 2005. Qualitative research methods: A data collector’s field guide. Research Triangle Park, NC: Family Health International. Available at: https://www.researchgate.net/publication/215666086_Qualitative_Research_Methods_A_Data_Collector's_Field_Guide [Accessed 6 June 2026].
Mandu, L.A. and Racoveanu, A.C. 2025. Artificial Intelligence and environmental law enforcement: can technology improve compliance with climate law? Law Review (Union of Jurists of Romania), Bucharest, pp. 267–286. Available at: https://www.proquest.com/openview/793ea432343d8cd0688a55ad1799326d/1?pq-origsite=gscholar&cbl=976338 [Accessed 1 June 2026].
Mashapu, L.D., Eboule, P.S.P. and Pretorius, J.H.C. 2022, June. The need for artificial intelligence for energy-efficiency management: A review. In 2022 8th International conference on energy efficiency and agricultural engineering (EE&AE) (pp. 1-6). IEEE. DOI:10.1109/EEAE53789.2022.9831359
Matlala, L.S. 2025. E-governance in South Africa: Barriers and enablers of virtual evaluation in the public sector. Insights into Regional Development, 7(2). DOI: doi.org/10.70132/d9854558432
Mlambo, F. and Mhlanga, D. 2022. Artificial intelligence and machine learning for energy in South Africa. AfricaGrowth Agenda, 19(3), pp. 20–23. Available at: https://ideas.repec.org/s/afj/journ2.html [Accessed 7 June 2026].
Moghayedi, A., Michell, K. and Awuzie, B.O. 2026. Analysis of the drivers and barriers influencing artificial intelligence for tackling climate change challenges. Smart and Sustainable Built Environment, 15(3), pp. 1277–1312. DOI: doi.org/10.1108/SASBE-05-2024-0148
Motsoeneng, M.T., Segooa, M.A., Motjolopane, I. and Kgopa, A.T. 2025. Robotic process automation readiness barriers and enablers in South Africa’s energy supply chain. Journal of Information Systems and Informatics, 7(3), pp. 3005–3024. DOI: doi.org/10.51519/journalisi.v7i3.1281
Mubangizi, J.C. 2024. Artificial intelligence, human rights and sustainable development: An African perspective. Perspectives of Law and Public Administration, 13(3), pp. 374–389. DOI: doi.org/10.62768/PLPA/2024/13/3/04
Mukelabai, M.D., Wijayantha, U.K.G. and Blanchard, R.E. 2023. Using machine learning to expound energy poverty in the global south: Understanding and predicting access to cooking with clean energy. Energy and AI, 13, article 100290. DOI: doi.org/10.1016/j.egyai.2023.100290
Murombo, T. 2022. Regulatory imperatives for renewable energy: South African perspectives. Journal of African Law, 66(1), pp. 97–122. DOI: doi.org/10.1017/S0021855321000206
Okonkwo, E., Ndu-Anunobi, G., Emecheta, C. and Alao, O. 2024. Harnessing artificial intelligence for sustainable development in Nigeria. International Journal of Public Administration and Development Studies (IJPADS), 1(1). Available at https://ijpads.com/index.php/ijpads/article/view/16 [Accessed 1 April 2026].
Ouedraogo, N.S. 2020. Transition pathways for North Africa to meet its (intended) nationally determined contributions ((I)NDCs) under the Paris agreement: A model-based assessment. Climate Policy, 20(1), pp. 71–94. DOI: doi.org/10.1080/14693062.2019.1685449
Pandey, R. 2002. Energy policy modelling: Agenda for developing countries. Energy Policy, 30(2), pp. 97–106. DOI: doi.org/10.1016/S0301-4215(01)00062-3
Radvilė, E. and Urbonas, R. 2025. Digital transformation in energy systems: A comprehensive review of AI, IoT, blockchain, and decentralised energy models. Energetika, 71(1), pp. 1–22. DOI: doi.org/10.6001/energetika.2025.71.1.1
Ramluckun, R., Malumbazo, N. and Ngubevana, L. 2024. A review of the energy policies of the BRICS countries: The possibility of adopting a just energy transition for South Africa. Sustainability, 16(2), article 703. DOI: doi.org/10.3390/su16020703
Sabatier, P.A. and Mazmanian, D.A. 1980. The implementation of public policy: A framework of analysis. Policy Studies Journal, 8(4), pp. 538–560. DOI: doi.org/10.1111/j.1541-0072.1980.tb01266.x
Shahiduzzaman, K.M., Jamal, M.N. and Nawab, M.R.I. 2021. Renewable energy production forecasting: A comparative machine learning analysis. International Journal of Engineering and Advanced Technology, 10(6), pp. 11–18. DOI: doi.org/10.35940/ijeat.e2689.0810621
Sibiya, B. 2023. Digital transformation of cities through emerging industry 4.0 smart technologies and infrastructure in South Africa. PhD thesis. University of Johannesburg. Available via ProQuest Dissertations and Theses (No. 31716202).
South Africa. Presidential Climate Commission (PCC). 2022. A framework for a just transition in South Africa. Pretoria: Presidential Climate Commission. Available at https://www.climatecommission.org.za [Accessed 1 June 2026].
South Africa. Department of Minerals and Energy. 1998. White paper on the energy policy of the Republic of South Africa. Pretoria: Department of Minerals and Energy. https://www.gov.za/sites/default/files/gcis_document/201409/whitepaperenergypolicy19980.pdf [Accessed 1 April 2026].
South Africa. Department of Minerals and Energy. 2003. White paper on the renewable energy policy of the Republic of South Africa. Pretoria: Department of Minerals and Energy. Available at: https://unfccc.int/files/meetings/seminar/application/pdf/sem_sup1_south_africa.pdf [Accessed 1 May 2026].
South Africa. Department of Energy. 2011. Integrated Resource Plan for Electricity (IRP) 2010-2030. Pretoria: Department of Energy. Government Gazette No. 34263, Notice 400 of 6 May 2011. Available at: https://www.energy.gov.za/IRP/2010/IRP2010.pdf [Accessed 28 May 2026].
Sutherland, E. 2020. The fourth industrial revolution – the case of South Africa. Politikon, 47(2), pp. 233–252. DOI: doi.org/10.1080/02589346.2019.1696003
Thopil, M.S., Bansal, R.C., Zhang, L. and Sharma, G. 2018. A review of grid connected distributed generation using renewable energy sources in South Africa. Energy Strategy Reviews, 21, pp. 88–97. DOI: doi.org/10.1016/j.esr.2018.05.001
Tinonetsana, F., Musariwa, P. and Madondo, E. 2024. Integrating AI for environmental sustainability in medium to large corporations: A case study of South Africa. International Journal of Business Ecosystem & Strategy, 6(6), pp. 15–21. DOI: doi.org/10.36096/ijbes.v6i6.643
Tokar, V. 2025. Artificial intelligence and economic security in EU macro-level smart energy systems: A sustainability-driven governance framework. Journal of Smart Energy Systems and Sustainable Technologies, 1. Available at https://zealpress.com/index.php/jsesst/article/view/737 [Accessed 6 June 2026].
Twinomurinzi, H., Msweli, N.T. et al. 2021. Digital skills in South Africa at the citizen level (Report RP56). Pretoria: Unisa Press, for the Knowledge for Innovation Unit (K4I), NEMISA, hosted at the University of South Africa (UNISA). Available at: https://unisapress.africa/index.php/unisapress/catalog/book/56 [Accessed 9 May 2026].
Vudugula, S. 2025. Sustainable smart supply chains: A review of green technologies and their impact on logistics. American Journal of Scholarly Research and Innovation, 4(1), pp. 1–32. Available at https://researchinnovationjournal.com/index.php/AJSRI/article/view/9 [Accessed 1 June 2026].
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 The Author(s)
This work is licensed under a Creative Commons Attribution 4.0 International License.
