07/15/2026 | Press release | Distributed by Public on 07/15/2026 10:21
The rapid growth and use of artificial intelligence (AI) is transforming many sectors, but it also has environmental implications that are complex and multifaceted. AI infrastructure drives increased demand for significant water use, greater energy consumption and expanded grid infrastructure, all of which require careful management to avoid environmental and community harm.
Energy and EmissionsU.S. data centers consumed 183 terawatt-hours (TWh) of electricity in 2024, more than 4 percent of the country's total energy usage, and that figure is projected to grow by 133 percent to 426 TWh by 2030. Virginia, Texas and Oregon had the highest emissions attributable to data centers. Typical AI research pipelines involve training thousands of models, resulting in cumulative emissions of tens of thousands of pounds of carbon dioxide (CO2) equivalent over several months. Training a single AI model can emit more than 626,000 pounds of CO₂ equivalent, nearly five times the lifetime emissions, including manufacturing, of an average American car. |
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WaterData centers consumed an estimated 17 billion gallons of water directly in 2023, with projections suggesting that use could double or quadruple by 2028. In 2021, 1 in 5 U.S. data centers was already located in an area experiencing water stress. Data center water use occurs both directly through cooling and indirectly through electricity consumption. Cooling alone can account for as much as 40 percent of a data center's total electricity consumption. Some facilities draw more than half of their water from potable sources and increasing data center capacity means water demand is likely to rise as computing infrastructure expands. |
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Grid ImpactIn the United States, fossil fuel dominated all electricity generated for data centers (56 percent), followed by renewable energy (22 percent) and nuclear power (21 percent). The growth of data centers is delaying coal plant closures, slowing or preventing national, state and local priorities to transition to clean energy, as renewable sources are insufficient to meet both hyperscale data centers and existing users' needs. |
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AI Task IntensityEmerging technologies, like AI, often require larger, more energy-intensive data centers to meet computational demand. Searches driven by generative AI use four to five times the energy of a conventional web search. Generative AI tasks such as text generation, summarization, image captioning and image generation tend to be more energy- and carbon-intensive than discriminative (predictive) use cases, such as using existing data in machine learning models to identify patterns, anticipate user behaviors and forecast upcoming events. |
Policy responses vary and often reflect a tension between furthering state-level economic development interests and balancing local community health and environmental concerns. States are primarily addressing energy reporting, ratepayer protection and environmental assessment. Local governments have tended to act more directly on land use, zoning and permitting, driven by community opposition and the immediacy of local resource impacts.
Select local actions include:
Public health practitioners are well-positioned to help navigate the tension between economic development and community health. The three core functions of public health, policy development, assessment and assurance, provide a concrete structure for that work:
The most consequential recommendation is also the most foundational, communities need the information, access and standing to participate in decisions about AI infrastructure that will affect their health for decades to come. Public health can serve as a valuable partner in shaping the ethical rollout of AI and emerging technologies in our increasingly digital society.
Download the full report to explore the findings in greater detail.
The Kansas Health Institute supports effective policymaking through nonpartisan research, education and engagement. KHI believes evidence-based information, objective analysis and civil dialogue enable policy leaders to be champions for a healthier Kansas. Established in 1995 with a multiyear grant from the Kansas Health Foundation, KHI is a nonprofit, nonpartisan educational organization based in Topeka.