AI's impact on the environment, and how to do better

More and more companies are using artificial intelligence to accelerate change and improve productivity. What not everyone realises yet is that the use of AI comes at a cost. Behind every AI-based tool sits a complex infrastructure that consumes electricity, water, and hardware on a scale most people never see.

Using AI without a clear idea of those costs does not align with environmental goals like striving to be sustainable, protecting nature, and reducing greenhouse gas emissions. To make economic growth and sustainability work together, GreenPT was founded.

The hidden environmental cost of AI

Whether you are using an AI-based virtual assistant, a generative model, or an automation pipeline, it all costs electricity, water, and raw materials. Especially large machine learning models require more energy every year as their complexity rises.

The expansion of AI places additional strain on global energy systems and contributes directly to carbon emissions. Both the United Nations Environment Programme and the International Energy Agency warn that energy consumption from technologies like AI poses a significant challenge for climate change.

The energy consumption of data centres

All digital services, cloud computing, and AI systems are ultimately driven by data centres. These are therefore major consumers of electricity. It is estimated that data centres amount to 3 percent of the world’s total consumption of electricity. That number is expected to rise.

A lot of that electricity is still generated by fossil fuels. This increases carbon dioxide emissions and accelerates climate change. The energy needed to power and cool AI data centres can also result in loss of biodiversity and have an impact on important ecosystems.

Older data centres in particular use outdated cooling techniques and hardware that is less efficient in its use of energy. This drives up the environmental footprint of conventional data centres even more.

The water usage of data centres

Most people do not know that data centres have to be cooled around the clock. Otherwise, the servers heat up too much. Traditional facilities rely heavily on cooling mechanisms based on water. Some data centres consume millions of litres of water every day.

In a world where clean water can be scarce, that is a hard statistic. It puts more pressure on local communities and natural ecosystems, especially in regions already affected by climate change.

The efficiency of water usage varies quite a bit between data centres. Modern facilities usually cool their servers more efficiently, which requires less water. That is why, ideally, your AI systems run in a sustainable data centre.

The acceleration of electronic waste

Next to energy and water, there is also the issue of electronic waste, also known as e-waste. As AI development accelerates, the life expectancy of hardware decreases. Data centres replace their servers quicker than they used to.

According to global estimates, electronic waste is now over 50 million tonnes per year. That number will continue to increase. Without proper waste management, dangerous materials such as lead, mercury, and lithium can leach into soil and water systems.

Those are major environmental concerns, and another reason to use AI mindfully. Companies with sustainability in mind should only use AI when they need to, and it is always better to run your systems in data centres powered by sustainable energy.

Worries about AI’s carbon footprint and climate change

Given the rise in energy consumption, water consumption, and e-waste, the carbon footprint of AI is higher than ever. Environmental protection organisations and policymakers call for sustainable strategies, renewable energy sources, and more efficiency.

If AI technologies keep relying on environmentally destructive ways of generating electricity, their contribution to climate change will outpace other digital sectors. Using AI sensibly is both an ethical responsibility and a practical necessity to meet climate commitments.

How GreenPT combines economic growth with sustainability

At GreenPT we are well aware of the impact of AI. We are also aware of the economic growth that AI brings about. That is why we decided to bring efficiency, sustainability, and privacy together in a sustainable GPT.

We prioritise sustainability in AI

Renewable energy fully powers our model. It runs on efficient data centres in the EU and is ISO-certified. We eliminate the use of fossil fuels, and that drastically lowers greenhouse gas emissions.

We also chose to use smaller, more efficient AI models. Our models are enhanced by compression and quantisation. That reduces computing power by 20 to 30 percent, without any noticeable quality loss.

We provide you with privacy

Next to sustainability, we also care about privacy. Our models and data centres strictly adhere to European laws, such as the GDPR. Data is not stored in third-party environments. We exclusively use self-hosted models on secure European servers.

No training data is ever harvested from user conversations. Conversations with GreenPT are protected by advanced encryption. With transparent data practices, we provide end-to-end security while maintaining minimal data collection.

We always strive for more efficiency

Last but not least, we are always aiming to make our systems more efficient. By making technical optimisations, we make our AI algorithms leaner and they use less energy. The model is advanced in reasoning, allows multilingual translation, speech-to-text, and much more.

We also provide real-time insights into energy usage. That helps organisations make more data-driven, sustainable choices that reduce the environmental footprint and align with company policies on energy efficiency and a sustainable future.

Performance metrics of GreenPT

GreenPT outperforms the industry average across the indicators that matter for environmental sustainability. Using our AI does less environmental harm and lines up well with supporting environmental goals.

When it comes to Power Usage Effectiveness (PUE), our data centres deliver a score of 1.37. That is well below the industry average of 1.55, which means a significantly higher efficiency in energy use.

Another important metric is Water Usage Effectiveness (WUE). Our data centres score 0.067, compared with the industry average of 1.8. That shows we use a lot less water, which is better for the environment.

And as mentioned before, our infrastructure is 100 percent powered by renewable energy. The renewable share in the industry overall is around 60 percent. Those numbers make GreenPT a leader in sustainable AI operations.

Why sustainable AI development matters more than ever

To reduce environmental risks and to support environmental goals, sustainable AI is no longer optional. It is a necessity for governments and companies that want to show they care about their energy infrastructure and the environmental impact of AI.

As artificial intelligence keeps spanning our digital economies, now is the time to make considerable changes and shape a sustainable future with AI. Choosing GreenPT is a practical, ethical, and economical step forward toward innovating responsibly.