Jakarta, INTI - The rapid expansion of Artificial Intelligence (AI) technologies is bringing unprecedented innovation and economic opportunities. However, a growing body of research suggests that the infrastructure supporting AI may come with a significant environmental cost. A recent United Nations report warns that the global surge in AI-driven data center development is placing increasing pressure on freshwater resources, a critical necessity for communities worldwide.
UN Warns of AI’s Growing Water Footprint
A report released on June 3, 2026, by the United Nations University Institute for Water, Environment and Health (UNU-INWEH) projects that the total land footprint of AI-related data centers worldwide could exceed 14,500 square kilometers by 2030. This area is roughly equivalent to twice the size of Greater Jakarta, a metropolitan region home to more than 32 million people.
The report further estimates that water consumption for cooling data centers could eventually match the annual basic domestic water needs of the entire population of Sub-Saharan Africa, which exceeds 1.3 billion people. According to UN researchers, this environmental cost has long been underestimated and inadequately measured in discussions surrounding digital infrastructure development.
The growing demand for electricity is another major concern. According to the International Energy Agency’s (IEA) report titled Energy and AI, data centers consumed approximately 415 terawatt-hours (TWh) of electricity in 2024, representing around 1.5 percent of global electricity demand. Since 2017, electricity consumption by data centers has grown at an average annual rate of 12 percent, more than four times faster than overall global electricity demand.
Global data center electricity consumption increased to 448 TWh in 2025. If data centers were considered a country, they would rank as the world's eleventh-largest electricity consumer, positioned just below France and ahead of Saudi Arabia.
The IEA projects that electricity demand from data centers will more than double by 2030, reaching approximately 945 TWh, nearly equivalent to Japan’s current annual electricity consumption.
Behind these figures lies the intensive cooling infrastructure required to keep computing systems operational. Data centers consume between 10 and 50 times more energy per square meter than conventional commercial office buildings, largely due to cooling requirements.
Cooling systems are among the largest contributors to water consumption. The IEA estimates that a 100-megawatt hyperscale data center in the United States consumes approximately two million liters of water per day, enough to meet the needs of around 6,500 households. More than 60 percent of this consumption comes indirectly through electricity generation processes.
Globally, data centers currently consume an estimated 560 billion liters of water annually. That figure is expected to increase to approximately 1.2 trillion liters by 2030 as demand for AI services continues to accelerate.
In some regions, the scale of water demand has already raised concerns among policymakers and utility providers. In Australia, Sydney Water reportedly received a connection request from a single data center seeking access to up to 40 million liters of water per day, equivalent to the volume of 16 Olympic-sized swimming pools.
Similar challenges are emerging across Southeast Asia. Johor Bahru, Malaysia, has become one of the most frequently cited examples of how AI infrastructure growth can strain local resources.
The Malaysian government introduced a temporary moratorium on certain AI data center developments due to concerns over balancing water availability between residential consumption, agricultural activities, and industrial demand.
“Johor Bahru is a notable example. The government imposed a moratorium on AI data center development because water resources must be shared between domestic consumption and the local palm oil industry,” said Hendra Suryakusuma, Chairman of the Indonesia Data Center Provider Organization (IDPRO), during a discussion in Jakarta.
Why AI Data Centers Require Massive Amounts of Water
The reason AI infrastructure requires such large amounts of water lies in the physics of high-performance computing. The more powerful and densely packed the processors used to train AI models become, the more heat they generate, requiring increasingly sophisticated cooling systems.
Hendra explained that for AI data centers operating above 32 kilowatts per rack, conventional air cooling is no longer sufficient.
As a result, the industry is increasingly adopting liquid cooling technologies, including direct-to-chip cooling, rear-door heat exchangers, and immersion cooling systems, where servers are submerged in non-conductive liquids to maximize heat dissipation efficiency.
“When we talk about hyperscale facilities with capacities exceeding 100 megawatts, they require millions of liters of water every month,” Hendra noted.
Indonesia’s Data Center Expansion Faces Sustainability Questions
Indonesia is currently accelerating the development of its data center ecosystem to support growing digital and AI-related demand. In Jakarta, the country’s primary data center market, operational co-location and hyperscale capacity reached 637.24 MW in the first quarter of 2026, with an additional pipeline of approximately 1.65 gigawatts under development.
According to the Jakarta Data Center Market Brief Q1 2026 published by IDPRO, Jakarta’s operational data center capacity has nearly doubled within two years, increasing from 288.99 MW in 2024 to 559.14 MW throughout 2025.
While AI promises transformative benefits across industries, experts warn that sustainable infrastructure planning must become a priority. Balancing technological advancement with responsible management of water and energy resources will be critical to ensuring that the AI revolution does not come at the expense of long-term environmental sustainability.
Conclusion
The rapid rise of artificial intelligence is driving unprecedented growth in data center infrastructure worldwide, bringing both economic opportunities and environmental challenges. As demand for computing power increases, so do the requirements for electricity and water, raising concerns about long-term sustainability. Experts emphasize that balancing AI innovation with responsible resource management will be essential to ensure that technological progress does not compromise water security, environmental resilience, and the well-being of future generations.
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