AI, Climate Change, and the Law: Why Regulating Technology’s Carbon Footprint Matters

Introduction

How many times do you use your AI chatbot in a day ?? Once , twice or maybe thrice but what’s the big deal behind it 🤔🤔
According to MIT technology review analysis report a simple search like “Tell me a joke” emits 57 joules per response which is equal to 0.3-4 grams of co2 depending heavily on model, hardware, and data‑center efficiency. Now imagine, if you asked for 100 short jokes in a day, that might be something like 30–400 grams of CO₂ in total, which is in the same rough range as driving a car for a couple of kilometers or running a small LED bulb for several hours. For one person this is tiny, but when millions or billions of people do thousands of queries, the total energy and CO₂ begin to look more like the carbon footprint of a small country’s data‑center electricity demand.
We never knew that a single search of our’s carries a hidden environment cost … it’s very unnoticed and easy to ignore but ignoring it won’t make it disappear.
This blog will reveal the invisible impact and explore what legal measures could turn use of AI cleaner and help us shape a more sustainable digital future.

Impact of AI’s carbon footprint

The carbon footprint of AI is the total amount of greenhouse gases emitted while performing various activities like answering various prompts, training models, creating images, and other activities. AI is significantly contributing to the world’s energy consumption. As of 2025, data centres already account for roughly 1–1.5% of all electricity used worldwide, and projections indicate this could rise to 3% by 2030. With AI workloads themselves now responsible for as much as 20% of global data-centre power demand, the environmental impact of AI is both real and growing.

According to the UN Environment programme report on “AI has an environmental problem” there are various impact of AI on environment some of them are as follows:

• Enormous Raw Material For AI Hardware
  Behind the convenience of AI lies massive physical footprint .For doing a small task to running AI models need a huge amount of natural resources. Like for manufacturing a computer of 2 kg we need 8 kg of raw materials but there’s a catch these raw materials are not just plastic or steel these are rare earth metals and minerals as the demand of AI is growing the need for hardware is also growing simultaneously which brings strain on the planet’s resources .
• Increase Of Electronic Waste And Toxic Pollutants
  With the evolution of AI systems older hardwares become obsolete and end up as electronic waste . These wastes do not degrade safely as they contain harmful substances like lead ,mercury and other harmful chemicals . If not disposed of responsibly (which happens often ) they can contaminate groundwater , soil,and ecosystem other then environment they also poses real threat to human health.
• High Water Use for Cooling and Running Data Centres
  Data centres use enormous amount of water for cooling and construction . Especially the ones which are running AI workloads use this more then others . In fact some estimates suggest that AI related infrastructure could soon use up to six times more water than Denmark a country nearly of 6 million people. This is concerning because globally still one quarter of population faces scarcity of proper drinking and sanitation facilities.
• Rise Of Energy Demands And Carbon Emissions
  The energy required for working of AI systems is massive in many regions of the world fossil fuels are still the major source of energy . According to the reports of International Energy Agency (IEA) even a single interaction with AI tools like chat GPT can consume upto 10 times more energy than a google search. This creates a direct relation between AI innovation and emission of greenhouse gases so there is an urgent need for action to protect our environment.

Legal Landscape

Artificial Intelligence is growing on a daily basis across the globe still many countries are not realizing the environmental impacts it leaves behind especially the growing carbon footprint , high energy use and electronic waste. Although Artificial Intelligence is promoted as a solution to many environmental damages but the harsh reality is that its own environmental impact is ignored by many nations in their national strategies. However, some countries have foreseen this issue and have come forward to take responsibility for creating sustainable and environmentally aware AI policies . These include :

• European Union
  The EU AI Act officially began on 1 August 2024, but its full impact will be seen by August 2026, giving the industry time to adjust. One important part of the Act, Article 40, tells standardisation bodies to create rules that help reduce the energy use and resource consumption of high-risk AI systems. Another key requirement is transparency—developers of General-Purpose AI models will now need to measure and report the environmental footprint of their systems, or at least provide clear estimates. The Act also connects with existing EU policies designed to improve energy efficiency in data centres and set eco-design standards for servers.
• The United States of America
  Although right now The U.S. doesn’t have specific environmental rules focused on AI, but it is using AI tools to strengthen existing laws like the Clean Air Act and the Clean Water Act. This helps the U.S. EPA monitor pollution and enforce regulations more efficiently. Alongside this, the National Institute of Standards and Technology (NIST) is working on sustainability guidelines for AI and assessing systems based on factors like energy use and carbon emissions. So while formal AI-environment regulations aren’t in place yet, groundwork is clearly being built for a more accountable and sustainable AI future.
• Australia
  Australia has taken a more structured approach by making safeguards compulsory for high-risk AI systems. This includes transparency, regular audits, and clear accountability. What stands out is that environmental protection isn’t treated as an afterthought—it’s built directly into Australia’s National AI Ethics Framework as a core value. In simple terms, Australia expects advanced AI to be responsible, trackable, and environmentally conscious from the start—not later as a correction.

India’s Current Position on AI & Sustainability

India is moving at a great pace in the world of AI, but when it comes to our policies, we still haven’t caught up with the environmental side of this. We are building a large number of AI data centers and startups that use a huge amount of resources, and there is no dedicated set of rules that keeps a check on AI’s carbon footprint. Our focus is still on innovation and scaling of AI in various sectors, not on the environmental issues that come with it.

The new Digital India Act is a step towards providing the country with a modern digital framework and fixing outdated tech laws, but it doesn’t directly address AI’s environmental impacts; it lays the foundation for transparent and responsible AI governance. The Digital India Act opens the door for India to introduce stronger policies that can cover eco-friendly AI policies as well.

Legal Reforms For Greener AI

As AI continues to grow current laws lag behind to ensure we keep up with the speed of technological development happening all over the world ,while also ensuring that our environment remains safe. We need some legal reforms to make sure that AI evolves responsibly so that we can protect both innovation and the environment at the same time .

• One of the changes we need is to make environmental transparency of AI companies mandatory. At this point of time the use of AI is becoming prominent in the world, from running AI models to building data centers. All of this leaves a large amount of carbon footprint, which is not known to people. It should be made compulsory for companies to openly report these numbers.
• Compulsory sustainability audits for high risk or large scale AI systems should be implemented. The vague claims of being “eco-friendly ” by companies should not be trusted instead independent government monitored audits that may make environmental impact measurable ,comparable and far more transparent.
• We need strong regulations for data centres that power AI, because they consume enormous amount of resources like electricity and water (especially for cooling) . Setting clear limits and guidelines can make AI infrastructure much more sustainable.
• Last but not the least there is a need for global standards that guide sustainable AI. Just like International climate agreements we need shared laws for how AI is built, trained and powered. As AI doesn’t operate within borders environmental impact from one country will affect the whole planet . Worldwide sustainable guidelines will help in growing Al in a way that supports the planet instead of harming it .

Conclusion

Ultimately, I would like to conclude that as AI continues to reshape our world, it’s becoming clear that innovation alone will not be sufficient. Ensuring that this process is both sustainable and responsible is as important. The AI footprint today is the smallest it will ever be, and it is our vigilance today that will either make or break our future. It is time we learn about things that create a long-term impact and work towards making a green and advanced future. Moving forward, transparency, sustainability audits, strong data center regulations, and global cooperation are no longer optional. AI is shaping the future, and the decisions we take today will decide our future. SO THE CHOICE IS YOURS……