Statutory, institutional, and policy reforms for a contextualised AI legal framework in West Africa’s renewable-energy sector

Machine learning is rapidly reshaping West Africa’s renewable-energy sector, offering advanced forecasting, grid optimisation, predictive maintenance, and distributed energy management. Yet, regulatory frameworks lag behind technological deployment, leaving oversight weak, accountability fragmented, and public protections underdeveloped. Unlike the European Union, which implements the Artificial Intelligence Act, West Africa lacks coherent statutory, institutional, and regional governance mechanisms. This paper proposes a multi-dimensional reform roadmap for ECOWAS member states, addressing statutory authorization, institutional capacity, regional coordination, procedural safeguards, and ethical obligations. It advocates a Regional Registry of High-Risk AI Systems to track cross-border deployment, support coordinated incident response, and enhance transparency and procurement fairness. Mutual recognition of AI certifications is recommended to harmonize standards, reduce vendor compliance burdens, and prevent regulatory arbitrage, thereby securing energy infrastructure while fostering regional integration under the West African Power Pool. Capacity building is positioned as a core regulatory safeguard. The framework distinguishes general AI literacy from machine-learning oversight competence, establishes minimum skill thresholds for regulators and judicial actors, and proposes phased, measurable targets for operational and regional technical capacity. Socio-technical rights are embedded into governance, operationalizing equality, privacy, procedural justice, and socio-economic protections in energy allocation and service delivery. AI-specific cybersecurity risks including data poisoning, adversarial attacks, and model theft, are addressed through tailored safeguards and institutional coordination. Procurement reforms balance enforceable obligations with aspirational goals, promoting transparency, interoperability, and local innovation while preventing dependency on foreign systems. By linking technical, legal, institutional, and socio-ethical dimensions, this paper provides a context-sensitive, actionable framework for sustainable, equitable, and accountable AI deployment in West Africa’s renewable-energy infrastructure.