AI Infrastructure Water Consumption Expected to Reach 2.27 Billion Cubic Meters by 2030

• June 11, 2026

As artificial intelligence (AI) technologies continue to expand, concerns about their environmental impact are mounting. A recent analysis highlights that by 2030, the water consumption linked to AI infrastructure could rise to approximately 2.27 billion cubic meters, driven largely by the increasing energy requirements of data center equipment.

Growing Water Demand Tied to Energy Usage

The projected water usage stems primarily from the cooling needs associated with data centers, which are the backbone of AI services. These facilities rely heavily on electricity to power and maintain the operation of servers and other hardware. As AI workloads increase, so does the associated power demand, which in turn escalates the volume of water required for cooling systems.

Data centers often utilize large-scale water cooling methods to dissipate the heat generated by servers. This process involves significant water consumption, making the environmental footprint of AI infrastructure multifaceted—not limited to just power usage but extending into resource management concerns such as water.

According to reports, the growth in AI-driven services and applications is expected to place added pressure on global water resources over the next decade. This rise in water consumption is largely indirect; it results from the energy needed to run and cool the sprawling facilities that support AI workloads rather than the AI technologies themselves.

Environmental experts emphasize that this trend exposes the importance of developing more energy-efficient data center operations and exploring alternative cooling solutions. These advancements could help mitigate the water footprint related to AI infrastructure growth.

As companies and governments continue to invest heavily in AI, the sustainability aspects of these technologies—including resource consumption—are becoming critical components of planning and evaluation. Innovations that minimize power consumption and enhance cooling efficiency will be key in managing the environmental challenges posed by expanding AI infrastructure.

While the figures underscore an accelerating resource demand, detailed strategies to balance AI development with environmental stewardship remain a dynamic area of research and industry focus.

AI infrastructure water use could hit 2.27 billion cubic meters by 2030, driven primarily by increased energy demand for data center hardware.