Energy infrastructure in conflict-affected regions faces a distinct set of pressures (physical attack, cyber intrusion and weak governance) that Artificial Intelligence (AI) alone cannot resolve. This paper sets out a Hybrid Human–AI Intelligence framework for energy security, tested against two contrasting settings: the highly digitised Gulf and the resource-constrained, fragmented infrastructure of Sudan.
The paper takes a qualitative, theory-driven approach, synthesising literature on AI-enabled energy systems, human–AI collaboration and energy security, and using two scenario analyses to develop a governance-oriented framework built around three operating modes: human-in-the-loop, human-on-the-loop and coactive teaming.
The research shows that while AI strengthens resilience through its predictive power, conflict settings sharpen its structural weaknesses, including cybersecurity exposure, data manipulation, black-box opacity, and automation bias. Human judgement, situational heuristics, and ethical decision-making are what keep these risks in check, with AI left to handle the routine computation.
Most existing work examines AI in stable energy infrastructure. This paper instead builds a conflict-sensitive framework that treats human governance as inseparable from the technical system, giving researchers and practitioners a structured way to design energy operations that stay resilient, trustworthy and accountable under instability.
The analysis is conceptual and based on secondary sources; empirical validation through field studies and quantitative evaluation is required.
The framework gives policymakers, energy operators and infrastructure planners a basis for deploying AI responsibly in critical energy systems, with direct implications for governance design, cybersecurity preparedness, institutional resilience and human-centred AI adoption in fragile settings.
Almubarak, I. A. A., Shazali, H. S. and Gaidoum, M. (2026): Strengthening Energy Security in Conflict-Affected Regions: A Hybrid Human–AI Intelligence Framework for Collaborative Governance in the Gulf and Sudan. International Journal of Innovation and Knowledge Management in Middle East and North Africa (IJIKMMENA), Vol. 11, Nos. 1/2, pp. 39-51.
