Applied Chemical Engineering

AI governance and digital transformation in public utilities: Evidence from Morocco’s national electric grid

Nissrine MAJIT

Laboratory of Mediation, Information, Knowledge and Society- MIKS: School of Information Sciences, Avenue Allal Al Fassi, Madinat AL Irfane, BP 6204, Rabat Institute, Morocco

Naila AMROUS

Laboratory of Mediation, Information, Knowledge and Society- MIKS: School of Information Sciences, Avenue Allal Al Fassi, Madinat AL Irfane, BP 6204, Rabat Institute, Morocco

Jamal MABROUKI

Laboratory of Spectroscopy, Molecular Modelling, Materials, Nanomaterials, Water and Environment, CERN2D, Mohammed V University in Rabat, Faculty of Science, AV Ibn Battouta, Agdal, Rabat 10106, Morocco

DOI: https://doi.org/10.59429/ace.v9i2.5938

Keywords: artificial intelligence; AI governance; smart grids; organisational acceptability; digital maturity; public utilities; critical energy infrastructure; Morocco

---

Abstract

Artificial Intelligence (AI) is increasingly used to support the digital transformation of critical energy infrastructures by improving forecasting, grid monitoring, predictive maintenance, and operational decision-making. However, AI deployment in public utilities faces challenges related to institutional acceptance, digital maturity, institutional trust, and governance mechanisms. This article investigates how these factors interact within Morocco’s National Office of Electricity and Drinking Water (ONEE). The methodology is based on 29 semi-structured interviews, thematic coding using NVivo, and an exploratory quantitative synthesis. The analytical framework combines a condensed UTAUT2 framework, the McKinsey AI Maturity Model, and selected AI governance dimensions related to accountability and interoperability. The findings suggest a positive association between AI maturity and organisational acceptability, with governance strengthening this relationship. However, given the qualitative-dominant design, the small sample size, and the exploratory scoring procedure, the correlation results are interpreted as indicative rather than confirmatory. The study contributes to applied infrastructure and utility governance research by showing that responsible AI deployment in critical energy systems requires not only digital capabilities but also transparent governance, regulatory clarity, cybersecurity safeguards, and internal stakeholder trust.

---

References

[1]. OCDE, Vers le numérique : Forger des politiques au service de vies meilleures. OECD, 2019. doi: 10.1787 /7cba1873-fr.

[2]. G. Vial, « Understanding digital transformation: A review and a research agenda », The Journal of Strategic Information Systems, vol. 28, no 2, p. 118-144, juin 2019, doi: 10.1016/j.jsis.2019.01.003.

[3]. K. Schumacher, F. Krones, R. McKenna, et F. Schultmann, « Public acceptance of renewable energies and energy autonomy: A comparative study in the French, German and Swiss Upper Rhine region », Energy Policy, vol. 126, p. 315-332, mars 2019, doi: 10.1016/j.enpol.2018.11.032.

[4]. ONEE. Rapport d’activité 2022. Office National de l’Électricité et de l’Eau Potable, 2022.

[5]. Royaume du Maroc. Loi n° 82-21 relative à l’autoproduction d’énergie électrique. Bulletin Officiel du Royaume du Maroc, 2025.

[6]. Royaume du Maroc. Décret n° 2-24-804 relatif aux compteurs intelligents. Bulletin Officiel du Royaume du Maroc, 2024.

[7]. O. V. Mathisen, M. E. Sørbye, M. Rao, G. Tamm, et V. Stantchev, « Smart energy in smart cities », in Smart Cities: Issues and Challenges, Elsevier, 2019, p. 283-307. Consulté le: 7 février 2025. [En ligne]. Disponible sur: https://linkinghub.elsevier.com/retrieve/pii/B9780128166390000168

[8]. C. Prades-Gil, J. D. Viana-Fons, X. Masip, A. Cazorla-Marín, et T. Gómez-Navarro, « An agile heating and cooling energy demand model for residential buildings. Case study in a mediterranean city residential sector », Renewable and Sustainable Energy Reviews, vol. 175, p. 113166, avr. 2023, doi: 10.1016/j.rser.2023.113166.

[9]. J. Knauf et J. Le Maitre, « A matter of acceptability? Understanding citizen investment schemes in the context of onshore wind farm development », Renewable and Sustainable Energy Reviews, vol. 175, p. 113158, avr. 2023, doi: 10.1016/j.rser.2023.113158.

[10]. N. Hinov, « A Maturity-Based Framework for Assessing the Level of Digitalization in Smart Grids », in 2025 International Conference on Information Technologies (InfoTech), Sofia, Bulgaria: IEEE, sept. 2025, p. 1-5. doi: 10.1109/InfoTech67177.2025.11175970.

[11]. A. Alsheibani, Y. Cheung, and C. Messom, “Artificial intelligence adoption: AI-readiness at firm-level,” PACIS 2018 Proceedings, 2018

[12]. M. J. Fell, D. Shipworth, G. M. Huebner, et C. A. Elwell, « Public acceptability of domestic demand-side response in Great Britain: The role of automation and direct load control », Energy Research & Social Science, vol. 9, p. 72‑84, sept. 2015, doi: 10.1016/j.erss.2015.08.023.

[13]. M. Tabaa, K. Alami, A. Dandache, Z. Benabbou, B. Chouri, et K. Bousmar, « Initiation à la conception et réalisation d’un réseau de capteurs intelligent : Maison Intelligente », J3eA, vol. 16, p. 1018, 2017, doi: 10.1051/j3ea/20171018.

[14]. Venkatesh, Morris, Davis, et Davis, « User Acceptance of Information Technology: Toward a Unified View », MIS Quarterly, vol. 27, no 3, p. 425, 2003, doi: 10.2307/30036540.

[15]. R. E. Freeman, Strategic management: a stakeholder approach, 2. [print.]. in Pitman series in business and public policy. Boston, Mass.: Pitman, 1984.

[16]. J. Gumz et D. C. Fettermann, « What improves smart meters’ implementation? A statistical meta-analysis on smart meters’ acceptance », SASBE, vol. 11, no 4, p. 1116-1136, déc. 2022, doi: 10.1108/SASBE-05-2021-0080.

[17]. OCDE, « Defining AI incidents and related terms », 2024.

[18]. S. S. S. R. Depuru, L. Wang, et V. Devabhaktuni, « Smart meters for power grid: Challenges, issues, advantages and status », Renewable and Sustainable Energy Reviews, vol. 15, no 6, p. 2736-2742, août 2011, doi: 10.1016/j.rser.2011.02.039.

[19]. T. Ahmad et al., « Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities », Journal of Cleaner Production, vol. 289, p. 125834, mars 2021, doi: 10.1016/j.jclepro.2021.125834.

[20]. World Bank. Digital transformation and opportunities for African businesses. World Bank, 2024.[21] CRE, « Rapport d’activité de la CRE 2022 », 2022.

[21]. Enerdata. China Energy Report. Enerdata, 2022.

[22]. M. Meliani, A. El Barkany, I. El Abbassi, A. Moumen Darcherif, et M. Mahmoudi, « Smart grid implementation in Morocco: Case study », Materials Today: Proceedings, vol. 45, p. 7675-7679, 2021, doi: 10.1016/j.matpr.2021.03.176.

[23]. M. Meliani, A. El Barkany, I. El Abbassi, et M. Mahmoudi, « Smart Grid Challenges in Morocco and an Energy Demand Forecasting with Time Series », JERA, vol. 61, p. 195-215, juill. 2022, doi: 10.4028/p-2gufv6.

[24]. T. Rhardas et H. Rochdane, « Factors Affecting Citizen Intention to Use Smart City Services in Morocco: A Systematic Literature Review and Conceptual Framework », in Advances in Marketing, Customer Relationship Management, and E-Services, L. Alla, A. Hmioui, et B. Bentalha, Éd., IGI Global, 2024, p. 114-138. doi: 10.4018/979-8-3693-3172-9.ch006.

[25]. R. Habachi, A. Boulal, A. Touil, A. Charkaoui, et A. Echchatbi, « Barriers to the Adoption of Smart Grids in Morocco », in Advanced Intelligent Systems for Sustainable Development (AI2SD’2019), vol. 624, M. Ezziyyani, Éd., in Lecture Notes in Electrical Engineering, vol. 624. , Cham: Springer International Publishing, 2020, p. 34-42. doi: 10.1007/978-3-030-36475-5_4.