2 Electric Grid Stocks to Buy as Soaring Artificial Intelligence (AI) Demand Drives Surging Electricity Demand
News Summary
The immense demand for Artificial Intelligence (AI) capabilities is driving a large-scale data center buildout expected to continue for years. This growth benefits not only AI chip companies like Nvidia but also significantly boosts demand for electricity infrastructure. Nvidia and OpenAI have struck a deal valued up to $100 billion, planning to deploy at least 10 gigawatts of Nvidia systems for OpenAI's next-generation AI infrastructure, a power demand equivalent to New York City's average electricity consumption. To support this increasing AI-related power demand, electric grids in the United States and other countries will require significant upgrades and expansion. The article highlights two electric grid-related stocks: GE Vernova and Quanta Services. GE Vernova's revenue grew 11% to $17.1 billion in the first half of 2025, with its electrification business jumping 19%, and approximately 25% of the world's electricity is generated by its customers using its technologies, with a current backlog of $129 billion. Quanta Services' revenue increased 22% to $13.0 billion in the same period, with its electric segment up 24%, and boasts a $35.8 billion backlog, having secured a major transmission line project with Idaho Power.
Background
The rapid advancement of Artificial Intelligence (AI) technology, especially the pursuit of generative AI and artificial superintelligence, is leading to an explosive growth in data center construction worldwide. These data centers have enormous energy demands, far exceeding traditional computing facilities, thus placing unprecedented strain on existing electric grids. The electric grid is an interconnected network encompassing electricity generation, high-voltage transmission, and low-voltage distribution. To meet the increased power load from AI, grids require extensive upgrades and expansion, including new transmission lines, enhanced substation capacity, and the integration of more diverse power sources. Companies like GE Vernova and Quanta Services are central players in providing these critical infrastructure and services.
In-Depth AI Insights
Is the true scale of AI's electricity demand being underestimated, and what implications does this have for the urgency of grid upgrades? - The article highlights that Nvidia and OpenAI's 10-gigawatt demand alone is equivalent to New York City's average power consumption, indicating that AI's electricity usage is not linear but exponential. The market may be broadly underestimating the long-term, cumulative demand for electricity infrastructure driven by AI. - This underestimation could lead to underinvestment and planning delays, especially given the lengthy approval cycles and massive capital expenditures involved in grid upgrades. - Considering the Trump administration's typical inclination towards deregulation to foster economic growth, this might accelerate approval processes but could also relegate environmental considerations or long-term sustainability planning to a secondary role, potentially creating unforeseen bottlenecks in the future. Beyond infrastructure providers, what 'hidden' beneficiaries or potential shifts in the competitive landscape should investors be watching? - On the surface, equipment manufacturers and engineering service providers like GE Vernova and Quanta Services are direct beneficiaries. However, within the power sector, particularly utilities with scalable clean energy assets, will gain a significant advantage as AI data centers increasingly seek sustainable energy solutions. - Large industrial gas companies (e.g., Linde, Air Products) may also indirectly benefit as data center cooling systems increase demand for specialty gases. Furthermore, advanced materials suppliers and automation solution providers play crucial roles in grid modernization. - The competitive landscape could trigger more M&A activity, with larger integrated energy service providers seeking to consolidate upstream and downstream segments to offer more comprehensive AI power solutions, thereby solidifying market positions. Given such immense investment demands, what long-term risks might investors be overlooking? - Regulatory and Policy Risks: While the Trump administration might promote infrastructure in the short term, state and local level resistance, along with potential shifts in energy policy, could lead to project delays or cost overruns. - Technological Obsolescence Risk: Rapid improvements in AI chip energy efficiency or the emergence of novel cooling technologies could partially decelerate the rate of electricity demand growth, impacting expected returns on current grid investments. - Supply Chain Bottlenecks: Critical equipment and materials needed for grid upgrades (e.g., high-voltage transformers, specialized cables) may face global supply shortages and geopolitical risks, leading to escalating costs and extended delivery times. - Rising Capital Costs: In a high-interest rate environment, the financing costs for large-scale infrastructure projects will significantly increase, potentially squeezing project margins and putting pressure on the financial health of utility companies.