Tech companies love to talk about efficiency gains, such as better chips, smarter cooling systems, and improved data center designs, but the math tells a different story. Even as individual AI systems become more efficient, the overall demand for generative AI is growing exponentially. Every new model, every surge in users, every additional application adds energy and water needs faster than efficiency improvements can keep up. In other words, the problem isn’t that AI itself is becoming more powerful, it’s that we’re scaling AI use far faster than we’re building the sustainable infrastructure needed to support it. Without careful planning, energy grids, water supplies, and local ecosystems will continue to feel the strain.

Addressing AI’s environmental impact isn’t hopeless, but it requires a deliberate shift in how we build and regulate the technology. Cities and states need to implement stricter oversight on where data centers are placed so that marginalized communities aren’t used as environmental sacrifice zones. AI companies should be required to publicly report their carbon emissions, water usage, and energy sources instead of offering vague sustainability claims.

At the policy level, AI expansion should be tied directly to the availability of renewable energy, preventing companies from defaulting to fossil fuels whenever demand spikes. At the same time, federal and state governments must invest in upgraded grid infrastructure that can support technological growth without worsening climate change.

Finally, community voices, especially Black, Brown, rural, and low-income residents disproportionately impacted by data-center pollution, need to be centered in every stage of decision-making. Too often, tech companies prioritize profit over people, dumping environmental and health costs onto vulnerable communities. The solution isn’t simply “cleaner technology”; it’s reevaluating whether and how we build AI at all, and ensuring that its deployment never comes at the expense of people or the planet.

AI doesn’t have to be destructive, but we can’t keep pretending its infrastructure is invisible. Most people only see the sleek interface, the chatbot, the app, the recommendation engine, without realizing the environmental toll hiding behind the screen. Gigantic data centers burn through guzzle electricity and guzzle millions of gallons of water, fossil fuel plants are fired up to meet skyrocketing demand, and communities near these facilities face polluted air, drained water supplies, and land stripped for massive server farms. This is not some abstract cost. It’s real, and it hits the most vulnerable hardest. If AI continues to be built on this low-road, high-impact model, we’re choosing a high-tech world powered by environmental exploitation. That’s a price none of us should be willing to pay.