As AI continues to transform our world in advanced ways, it is so important to confront its environmental costs and innovate sustainable solutions, because AI is not going away. In fact, AI is the future of technology; therefore must be built to coexist with the future of our planet. 

According to ScienceNews, training a single artificial intelligence model requires as much electricity as 100 U.S. homes in one year. Along with that, the AI machines require gallons of water to keep the data centers cool. With AI technology on the rise, many people are captivated by its exciting potential and the promise associated with it. From boosting productivity in the workforce to transforming research strategies, AI is reshaping our world in so many ways. Despite the excitement surrounding this evolving technology, the environmental impacts are often not acknowledged.

What is AI?

To understand the effects AI has on our environment, we first need to address what AI is and what people use it for. AI stands for artificial intelligence, which is the simulation of human behavior and intelligence in machines. These machines are programmed to do anything from simple performance tasks, such as decision-making, to more complex tasks, such as transportation. 

AI Transforming Our Future 

In just a few years, AI has skyrocketed in popularity and capability. According to Stanford University’s 2025 AI Index Report, AI has become more integrated in our lives than ever before. Businesses are investing at record levels, and global optimism surrounding AI has increased significantly. The promise of AI is undeniable: improved worker productivity, breakthroughs in science, and unique opportunities for innovation. While these advancements deserve great recognition, there is a side that is left in the shadows and not considered as much as it should be.  

Environmental Cost of AI 

Behind sleek chatbots like ChatGPT and Google Gemini lies a concerning environmental footprint. Developing these AI machines requires absurd amounts of energy, which contributes to rising carbon dioxide emissions and, therefore, global warming. On top of that, there is a great deal of water needed to cool down the hardware, which threatens municipal water supply as well as local ecosystems. 

To put this into perspective, “The Uneven Distribution of AI’s Environmental Impacts” by Harvard Business Review explains the environmental effects in a more comprehensive way. 

“The training process for a single AI model, such as a large language model, can consume thousands of megawatt hours of electricity and emit hundreds of tons of carbon. This is roughly equivalent to the annual carbon emissions of hundreds of households in America,” (Wierman, 2024). 

To put it plainly, every new advancement in AI is followed by a hidden environmental bill. Although we cannot see it, this technology is actively contributing to global warming and resource depletion. It is also important to note that carbon dioxide emissions remain in the atmosphere for centuries, which makes the effects practically irreversible and long-lasting. 

AI in Context

It is important to note that AI is not the first digital technology to spark controversial environmental debates. For instance, cryptocurrency mining involves powerful computers solving complex problems to validate various transactions and create new digital coins. This process, like AI data machines, requires an absurd amount of electricity, which strains local power grids and is also a large participant in adding to carbon emissions. However, as AI adoption continues to increase, its energy and water use may surpass that of crypto. Most importantly, AI’s environmental footprint is especially concerning because it is not visible to the human eye– you do not see the emissions when you ask ChatGPT a question. 

What Can We Do To Help?

While the severe environmental impact of AI may seem daunting, here are some steps of action you can take into consideration: 

1. Encourage sustainable AI development: tech companies should start prioritizing sustainable energy sources and energy-efficient model designs 
2. Start investing in renewable energy: transitioning data centers towards solar, wind, and other clean energy sources to start cutting down on emissions.
3. Increase transparency on this issue: companies should normalize being transparent about environmental costs, allowing customers to make more informed decisions.  
4. Become more mindful users: as consumers, we can reduce our usage of AI and commit to more sustainable practices in our everyday lives. 

Moving Forward

Although AI holds a hefty promise, every innovation comes with a hidden cost. I am a strong believer that acknowledging AI’s environmental footprint is not a rejection of this technology, but rather an opportunity to innovate new ways for technology and sustainability to coexist. AI is not going away anytime soon, so if we take the time now to educate ourselves, we can create new alternatives to sustain the enormous energy requirements to fuel these powerhouse machines.