On emissions, 2025 survey data underscores that senior leaders remain confident in AI’s long-term environmental benefits, even as the pace of progress might be tempered by the realities of implementation at scale. Notably, AI is now being deployed in critical areas such as methane detection and carbon capture—two cost-effective and scalable levers for decarbonization. Methane, while less abundant than CO₂, is much more potent as a greenhouse gas over a 100-year period, making rapid detection and mitigation a top priority for the sector. AI-powered systems enable real-time monitoring and swift response to leaks, helping organizations like ADNOC and its partners prevent emissions, optimize energy use, and monitor carbon storage with enhanced accuracy. At the same time, carbon capture, utilization, and storage (CCS/CCUS) is increasingly recognized as essential for decarbonizing hard-to-abate sectors such as cement, steel, and chemical industries where direct emissions reductions are challenging. Here, AI is accelerating progress by optimizing capture processes, improving site selection, and enhancing monitoring and verification. ADNOC and partners are deploying machine learning to prevent leaks, “ AI can be a powerful driver for an equitable energy transition in Africa. By optimizing renewable energy generation and grid management, it will help countries leapfrog directly to cleaner, more efficient systems, reducing waste and reliance on fossil fuels. This must be done alongside investment in people and infrastructure – prioritizing digital skills, expanding broadband and reliable power grids, and building the data centers required to run these systems. The ambition and intent is in place; we must now focus on building the partnerships required to deliver the promise of energy for AI.” Carlos Lopes Professor at Nelson Mandela School of Public Governance, University of Cape Town 10