At the same time, AI is emerging as a large-scale energy consumer, with next-generation campuses requiring considerable power capacity. Data centers, while currently accounting for a small share of global electricity use (about 1.5% in 2024) 4 , are seeing their local and global impact rise rapidly due to surging investment and the growth of AI where certain types of AI-focused data centers can consume as much electricity as some heavy industry segments. According to the IEA, electricity use by data centers is projected to more than double to around 945 terawatt hours (TWh) by 2030, driven largely by AI workloads. 5 This shift is changing collaboration among energy companies and digital infrastructure providers. Data centers are no longer niche IT loads; they are an emerging, innovative class of infrastructure that must be planned hand-in-hand with energy company partners and in the local communities in which datacenters operate. Electricity grids are already under strain in some areas, and unless addressed, planned data center projects in certain Tier 1 infrastructure markets could face delays due to delays in grid upgrades. Moreover, certain types of grid bottlenecks may constrain clean energy coming online to support data center builds. Siting decisions can also determine whether growth reinforces resilience or deepens stress on aging grids, especially in markets where key infrastructure, such as transformers, begin to reach in- service retirement. Data center operators and electric utilities are becoming aware of the speed and scale of system changes required to meet cross-industry growth, necessitating a broad spectrum of scalable and sustainable approaches. As part of this transformation, companies such as Microsoft are helping accelerate the deployment of carbon-free AI-augmented reinsurance (RIQ partnership) ADNOCs $500 million partnership with RIQ, an AI-native reinsurance platform, marks a significant step toward modernizing risk management in the energy sector. This collaboration is focused on developing capital-efficient insurance solutions that leverage AI to assess, structure, and price coverage for both climate and operational risks interwoven challenges that are especially acute in emerging markets. 6 ENERGY ai A collaboration between ADNOC, AIQ, G42, and Microsoft, ENERGY ai is designed to harness the power of agentic AI for the energy sector. At its core, ENERGY ai leverages autonomous AI agents to manage complex and data-intensive tasks such as seismic analysis, reservoir modeling, and emissions forecasting. By automating these traditional labor- intensive processes, the platform accelerates decision- making and improves the accuracy of subsurface and operational insights. This supports more precise emissions tracking and reporting as well as enhancing the efficiency of exploration and production activities. By providing advanced AI-driven tools, ENERGY ai is helping to democratize access to cutting-edge technology, enabling a broader range of stakeholders to participate in the global energy transition. 7 AI-powered infrastructure for industrial growth Expectations for AI's energy consumption Figure 3 Business Leaders believe more strongly than Business Decision Makers that AI will increase energy consumption in both the near and distant future Impact of AIs Adoption on Energy Consumption in 2030 Impact of AIs Adoption on Energy Consumption in 2050 60% 27% 12% 2024 71% 16% 12% 1% 2025 Causes Decrease in Total Energy Used Dont Know Causes an Increase in Total Energy Used Have No Impact 2024 54% 16% 27% 2% 2025 40% 14% 47% 1% 11%+ 14%+ 11%+ electricity to the grid through innovative procurement strategies and policy engagements. These efforts include power purchase agreements (PPAs) that enable the addition of net-new, reliable, carbon- free electricity to regional grids, while also supporting a diverse zero-carbon energy mixspanning wind, solar, geothermal, clean hydrogen, sustainable biomass, energy storage, nuclear, and fusion technologies. Such approaches are essential to building a resilient and flexible grid capable of supporting region-specific data center expansion and broader electrification goals. The dual transformation of AI and energy presents both opportunity and risk. For energy companies, AI offers operational efficiencies, emissions reduction, and potential new revenue streams. For AI providers, reliable and low-carbon power supply is now a strategic differentiator. But the risks of unclear investment pathways, regulatory barriers, and workforce shortages are real. Without purposeful action, the AI era could face obstacles to realizing its transformational potential on a rapid timeline.. The path forward is clear: accelerate cross-sector collaboration, invest in flexible and resilient infrastructure, build the workforce of the future, and establish governance frameworks that ensure AI and energy scale responsibly. AI for Energy and Energy for AI are no longer separate agendas; they are mutually reinforcing imperatives. The challenge, and the opportunity, is to harness synergies to deliver a sustainable and secure energy future. 2025 SURVEY INSIGHT 4 IEA Energy and AI report, April 2025, https://www.iea.org/reports/energy-and-ai 5 IEA Energy and AI report, April 2025, https://www.iea.org/reports/energy-and-ai 6 ADNOC, RIQ Strike $500M AI-Driven Reinsurance Deal To Boost Abu Dhabis Role In Global Risk Finance, September 2025, https://www.forbesmiddleeast.com/money/banking-finance/adnoc-riq-strike-%24500m-ai-driven-reinsurance-deal-to-boost-abu-dhabis-role-in-global-risk-finance 7 ADNOC and AIQ Developing First-of-a-Kind Agentic AI Solution for Global Energy Transformation, November 2024, https://www.adnoc.ae/en/news-and-media/press-releases/2024/adnoc-and-aiq-developing-first-of-a-kind-agentic-ai-solution-for-global-energy-transformation 19 Powering Possible 2025 18