Investing in AI-specific energy needs presents opportunities for regional countries
- Estimates project energy consumption to double to 945 terawatt-hours by 2030... and reach 1,200 terawatt-hours by 2035
- Data center electricity consumption is poised to account for one-eighth of total demand in the United States
- With the help of artificial intelligence, up to 175 gigawatts of transmission capacity can be unlocked without new power lines
In its Thought Leadership report series, National Wealth Company noted that the artificial intelligence (AI) narrative over the past few years has centered on software and electronic chips: models capable of writing, coding, and logical reasoning, along with the processors trained to run them. During this phase, electricity was treated as a secondary operational input, receiving little attention from investors. However, the rapid expansion in the adoption of AI applications has altered this equation; the primary challenge is no longer limited to the capabilities of electronic chips, but now lies in securing adequate energy supplies and providing the physical infrastructure necessary to support large-scale operations.
The report stated that the amounts invested are substantial enough to directly impact investment portfolios. According to estimates by the International Energy Agency (IEA) regarding data center capacity, cumulative investments are projected to reach approximately $3.9 trillion by 2030.
The report also highlighted that data centers are estimated to consume 485 terawatt-hours (TWh) in 2025, representing about 1.5% of global electricity consumption (according to the IEA). However, more significant than the current share is the pace of growth. Leading estimates project that consumption will more than double to reach approximately 945 TWh by 2030—slightly exceeding Japan’s current total consumption—before rising to 1,200 TWh by 2035.
After data center electricity consumption constituted a marginal share of national demand just a few years ago, it is now poised to represent roughly one-eighth of total electricity demand in the United States in the coming years.
The report noted that electricity demand is transforming the industry from an intangible, virtual sector into a purely physical one. Large-scale AI operation requires power generation.
No single fuel source dominates the landscape. Moreover, power grids have become a major bottleneck for expansion, a situation that benefits entities capable of providing effective solutions to these challenges. Developing new transmission lines in advanced economies takes between four and eight years, while wait times for transformers and cables have doubled over the past three years.
With the assistance of artificial intelligence, up to 175 gigawatts of transmission capacity can be unlocked without the need to build new lines.
The report addresses the scale of spending required to finance these projects. The estimated $3.9 trillion over the next five years is too large to be covered by corporate budgets alone.
According to Vanguard data, the average annual total debt issuance by the top five technology hyperscalers was approximately $35 billion per year between 2020 and 2024, before jumping to $93 billion in 2025 and reaching approximately $132 billion in the first seven months of 2026.
New financing structures are emerging alongside debt; in August 2026, Nvidia announced partnerships with several global asset managers to launch platforms aimed at attracting over $500 billion in investor capital, providing cloud operators and institutions with dedicated financing resources for Nvidia-based systems.
For diversified investment portfolios, the true and largest exposure to this sector may lie in infrastructure, private credit, and tangible assets, rather than being limited to listed technology stocks in financial markets.
The report argues that this transformation directly impacts investors in the region. The International Energy Agency (IEA) projects that more than half of the energy consumed by data centers will be located outside the United States, as operators seek energy, land, and greater control over computational resources.
Gulf states emerge as among the biggest beneficiaries of this global shift. Saudi Arabia’s HUMAIN aims to develop artificial intelligence (AI) data center capacity of up to 1.9 gigawatts by 2030, expanding to 6.6 gigawatts by 2034. Meanwhile, the UAE has announced the establishment of a 5-gigawatt complex in Abu Dhabi, one of the largest AI data center projects outside the United States. Qatar has also allocated significant investments to expand its large-scale data center capabilities. The region enjoys several competitive advantages, including relatively low energy costs, advanced telecommunications infrastructure, and a strategic geographic location that provides access to a broad segment of the global population. For regional investors, these developments represent an exceptional opportunity to capitalize on one of the most significant global structural trends, which is taking shape and growing in their immediate vicinity.
The report warns that the growth path is not free from challenges, necessitating a careful assessment of the associated risks.
The first risk lies in the level of demand itself. Projections for AI-related electricity consumption rely on assumptions regarding technology adoption rates, revenue-generating capabilities, and operational efficiency levels. These parameters may change over time, particularly if rapid advancements in chip design and intelligent models lead to a faster-than-expected reduction in energy consumption.
The second risk concerns execution efficiency. Challenges related to connecting projects to power grids, long lead times for critical equipment supply, and shortages of specialized skills and labor could delay the implementation of many projects. IEA estimates indicate that a significant portion of the planned additional data center capacity faces delay risks due to these factors.
The third risk is financial. The infrastructure supporting AI requires massive capital investment, making future returns highly sensitive to any deviation in underlying assumptions. There is also a significant social and regulatory dimension; rapid growth in electricity demand, if not managed efficiently, could lead to higher energy costs for households and businesses, potentially prompting further regulatory intervention and oversight.
Despite the importance of these risks, they do not alter the sector’s overall growth trajectory but rather underscore the need to treat it as a long-term investment opportunity in infrastructure.
1. The primary bottleneck for AI is shifting from chips and software to electricity and physical infrastructure, transforming the sector from a virtual industry into a story of energy and tangible assets.
2. Global demand for data center electricity is expected to more than double, from approximately 485 terawatt-hours in 2025 to around 945 terawatt-hours by 2030. The United States is projected to account for 9% to 17% of its national energy consumption by 2030, compared to approximately 4–5% currently.
3. Meeting this demand will rely on renewable energy, natural gas, and nuclear power in the future, reviving utilities, energy equipment, and grid infrastructure as growth sectors after decades of stagnation.
4. The scale of investments required by 2030 is too large for technology companies’ balance sheets to bear alone, opening the door for infrastructure investors, private credit, and tangible assets rather than limiting exposure to listed tech equities.
5. The Gulf region emerges as a key hub as capacity shifts beyond the United States, offering regional investors the opportunity to gain exposure to a global trend close to home.
6. The risks are real: broad uncertainty over the scale of AI demand, grid and equipment bottlenecks, and high capital intensity all call for a long-term, diversified approach rather than concentrated, direct bets.
