The Role of Energy in Data Centers and the AI Boom
Former U.S. President Joe Biden is facing a worsening health situation after his son Hunter Biden said the cancer has spread to his bones and described the disease as "very painful" and "very debilitating."
As demand for artificial intelligence grows, the energy industry faces a challenge: how to power expanding digital infrastructure without placing excessive pressure on electricity grids, water supplies, and climate goals.
Q. Why does artificial intelligence need so much energy?
Artificial intelligence may appear to operate entirely online, but its services depend on physical infrastructure. Data centers are facilities filled with servers, storage systems, networking equipment, and cooling systems that process and store digital information.
Training large AI models requires powerful computer chips to process enormous amounts of data. Once a model is available to the public, every request also requires computing resources. Millions of requests, alongside other data center services such as cloud storage and video streaming, contribute to overall electricity demand.
According to the International Energy Agency (IEA), global data center electricity consumption increased by 17% in 2025, while electricity use by AI-focused data centers rose by 50%. The figures show how rapidly demand is growing as AI becomes more widely used.
Q. How much electricity could data centers consume in the future?
The IEA's 2026 analysis projects that global data center electricity consumption could nearly double, from approximately 485 terawatt-hours (TWh) in 2025 to 950 TWh by 2030. That would account for around 3% of global electricity demand by the end of the decade.
The growth is not driven by AI alone. Cloud computing, online services, digital storage, and other computing activities also require electricity. However, A
These projections are not guaranteed. Improvements in computing efficiency, changes in AI adoption, supply-chain constraints, and delays in constructing new facilities could all affect how quickly electricity use rises.
Q. What happens when data centers need more power than local grids can provide?
Data centers require a stable electricity supply because interruptions can disrupt digital services and computing operations. But new facilities can require large amounts of power in locations where electricity networks were not designed to accommodate such demand.
Building new power plants, transmission lines, substations, and transformers can take years. As a result, some proposed data centers face delays while waiting for grid connections and additional generating capacity.
The pressure can also raise questions about electricity affordability. Grid upgrades and new power infrastructure cost money, and policymakers must determine how those costs should be shared between data center operators, electricity companies, governments, and other consumers.
Q. Can renewable energy power the AI boom?
Renewable energy sources, including solar, wind, and hydropower, can supply electricity to data centers. Technology companies have increasingly signed power purchase agreements to support renewable energy projects, while some are exploring nuclear power and other sources that can provide electricity more consistently.
However, purchasing renewable electricity does not automatically mean a data center runs entirely on clean energy at every hour. Solar and wind generation depend on weather conditions, while data centers generally need continuous power. Energy storage, stronger transmission networks, and reliable low-emission electricity sources can help close that gap.
The IEA's 2025 Energy and AI report projected that renewables would meet nearly half of the additional electricity demand from data centers through 2030 in its central scenario. Natural gas, coal, and nuclear power are also expected to contribute, with the mix varying by region.
Q. Why are water use and cooling also major concerns?
Powerful computer chips generate heat, so data centers need cooling systems to prevent equipment from overheating. Depending on the facility's design, cooling may involve air, water, or liquid-based systems. Water can also be consumed indirectly when electricity is generated at power plants.
The amount of water required varies widely according to cooling technology, climate, server efficiency, and the local electricity supply. A 2025 study published in Resources, Conservation and Recycling found that water use per computing workload can vary by more than 10,000 times under different conditions.
This makes it difficult to assign one water-use figure to every AI request or data center. Still, locating facilities in water-stressed regions can create additional concerns for nearby communities, particularly where water is already needed for households, farming, and industry.
Q. Can AI help solve the energy problems it creates?
AI can also be used to improve the systems that supply electricity. Utilities can apply AI tools to detect equipment problems, forecast electricity demand, monitor grid conditions
, and help manage renewable energy sources.
These applications could improve efficiency and reduce some operating costs. However, the benefits depend on how well the technology is implemented, and using AI to manage energy systems does not eliminate the electricity required to run the AI itself.
The challenge is to ensure that efficiency improvements translate into meaningful reductions in energy use rather than being offset by growing demand for more computing services.
Q. How can countries balance AI development with energy security?
Governments and energy companies must plan for data center growth before electricity shortages and infrastructure delays become more severe. This includes improving grid capacity, expanding low-emission electricity generation, strengthening energy storage, and establishing clear rules for how large facilities connect to power networks.
Data center operators can also help by improving server efficiency, choosing appropriate locations, reporting energy and water use, and adjusting certain computing tasks to periods when electricity is more readily available.
The central issue is not whether AI will consume energy, but how responsibly that energy will be produced and used. Data centers are becoming essential infrastructure for the digital economy, yet their expansion must be weighed against electricity affordability, water availability, environmental impacts, and the needs of surrounding communities.
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