***AI Is Not Nearly as Bad for the Environment as People Claim - What the Data Actually Shows
AI has become a very controversial subject. One of the most common criticisms is that AI is extremely harmful to the environment, consumes huge amounts of water and electricity, and is going to cause an environmental disaster.
Some of these concerns are legitimate. AI does consume electricity, requires data centers, uses hardware and can have an environmental footprint.
However, many claims circulating online simplify or exaggerate the available data.
My goal here is not to claim that AI is environmentally harmless. It clearly is not. The goal is to separate what we actually know from exaggerated claims.
- AI does consume electricity
According to the International Energy Agency, data centers as a whole consumed around 415 TWh of electricity worldwide in 2024, around 1.5 percent of global electricity consumption.
It is important to remember that AI represents only part of data-center activity. Data centers also run cloud services, websites, storage, streaming, business software and many other services.
The IEA expects global data-center electricity consumption to approach around 950 TWh by 2030.
AI is one of the main drivers of this increase.
So saying "AI uses electricity" is obviously true.
But saying "AI consumes a huge percentage of the world's electricity" is misleading.
The global share is still relatively small, even though the growth rate is significant.
- There is no universal energy cost for one AI question
Another common claim is that every AI prompt consumes a huge amount of electricity.
There is no single number that applies to every AI query.
Energy consumption depends on the model, hardware, data center, cooling system, length of the request, complexity of the task and electricity source.
A simple text request is not equivalent to generating a high-resolution video or asking an AI system to perform a complex multi-step task.
The IEA has reported very large improvements in the energy efficiency of AI tasks because of improvements in hardware and software.
This means that older estimates should not automatically be presented as if they describe today's AI systems.
At the same time, more advanced AI workloads can consume substantially more energy.
The correct conclusion is therefore that AI has an energy cost, but there is no universal "energy cost per AI question."
- What about water?
This is a legitimate concern.
Data centers can use water for cooling, and electricity production can also have a water footprint.
However, water consumption depends heavily on location, climate, cooling technology, electricity source and infrastructure.
This means that a data center in a hot region suffering from water scarcity can have a very different local impact from one using a different cooling system in a region with abundant water.
Some studies have estimated significant water footprints for particular AI models.
For example, research concerning GPT-3 estimated that around 500 ml of water could correspond to approximately 10 to 50 medium-length responses under specific assumptions.
But this does NOT mean that every AI question today consumes half a liter of water.
It was a modeled estimate for a particular conditions.
Therefore, statements such as "every AI prompt uses a bottle of water" should not be treated as universal scientific facts.
- AI is not consuming all of the world's water
The previous point is important because online discussions sometimes transform specific estimates into claims about the entire planet.
AI can create significant water demand in certain locations.
That is a real environmental issue.
But there is no evidence that AI is simply "draining the world's water supply."
The environmental impact of data centers is highly dependent on where they are built and how they operate.
This is why local water availability matters much more than a single global number.
- What about CO2?
Data centers also create indirect CO2 emissions because they consume electricity.
According to the IEA, data centers were responsible for roughly 180 million tonnes of indirect CO2 emissions from electricity consumption in 2024.
That is a significant amount.
However, it represented around 0.5 percent of global emissions from fuel combustion.
This does not mean that the emissions are irrelevant.
It means that claims such as "AI is one of the main causes of climate change" go far beyond what the current data supports.
The electricity source also matters.
A data center powered mostly by low-carbon electricity does not have the same carbon footprint as one relying heavily on coal or natural gas.
- What about minerals and electronic waste?
AI requires GPUs, servers, networking equipment and other electronic components.
Producing these components requires raw materials and has environmental consequences.
Mining can cause pollution, habitat destruction and greenhouse-gas emissions.
Electronic waste is also a real problem.
However, AI is not responsible for the entire environmental impact of the electronics industry.
The same materials are used to manufacture computers, smartphones, electric vehicles, telecommunications equipment and many other technologies.
The UNEP has also pointed out that there is still limited data allowing researchers to determine exactly how much mineral demand and electronic waste can be attributed specifically to AI.
So the responsible conclusion is that AI contributes to these problems, but the exact size of its contribution is still difficult to measure.
- AI can also have environmental benefits
This part is often missing from discussions about AI.
AI can potentially be used to optimize electricity grids, improve renewable-energy forecasting, improve industrial efficiency, detect methane emissions, optimize infrastructure and assist with scientific research.
The IEA has estimated that some AI applications could potentially produce emissions reductions that are larger than the emissions associated with data centers themselves.
However, these benefits are not guaranteed.
AI can also create additional demand for energy and resources.
The important point is simply that AI is not exclusively an environmental burden.
Its environmental impact depends partly on how it is used.
- The efficiency paradox
AI models are becoming more efficient.
However, if AI becomes cheaper and easier to use, people may use it much more.
This is known as a rebound effect.
For example, if the energy required for one AI task decreases dramatically but the number of AI tasks increases even faster, total energy consumption can still rise.
This is one reason why improving efficiency does not automatically solve the environmental problem.
But it also means that saying "AI is becoming more efficient, therefore nothing is wrong" would be incorrect.
The situation is more complicated.
- "AI is stealing artists' jobs"
This is another major criticism of AI.
There is a real issue here.
AI image, music, video and writing tools can automate certain tasks that were previously performed by human workers.
Some companies may use AI to reduce the amount of human labor required for certain projects.
Some artists may lose certain types of commissions because clients can now generate acceptable results more cheaply.
It would be dishonest to pretend that this never happens.
However, "AI is stealing artists' jobs" is far too broad a statement.
- Automating tasks is not the same as replacing an entire profession
The creative industries contain many different jobs.
Illustrators, concept artists, animators, photographers, graphic designers, 3D artists, video editors, art directors and many others perform very different tasks.
AI does not affect all of these jobs in the same way.
Generating a simple image is not necessarily equivalent to performing the entire job of a professional artist.
Professional creative work can involve understanding a client's objectives, developing concepts, making creative decisions, communicating with a team, maintaining consistency, responding to feedback and making precise revisions.
AI can automate some of these tasks.
But that does not automatically mean that the entire profession disappears.
Technology has historically automated parts of many professions without eliminating the profession .
- Does this mean artists have nothing to worry about?
No.
Some artists can genuinely be negatively affected by AI.
Some entry-level and repetitive creative tasks may become less valuable.
Some clients may choose AI instead of hiring a human for certain projects.
That is a legitimate concern.
The important distinction is between saying:
"AI is changing the demand for some creative work."
and
"AI is going to replace artists."
The first is already happening in some areas.
The second is a prediction, not an established fact.
- AI training and artists' work are a separate issue
Another important debate concerns the data used to train AI models.
There are legitimate questions about copyright, licensing, compensation and whether creators should have meaningful ways to opt out.
These issues deserve serious discussion.
But they should not automatically be treated as proof that AI will eliminate artistic professions.
There are actually several separate questions:
How are AI models trained?
Can copyrighted material legally be used for training?
Should creators be compensated?
Should creators have opt-out mechanisms?
How will AI affect employment in creative industries?
These are related questions, but they are not the same question.
- The most reasonable conclusion
I do not think the evidence supports either extreme position.
"AI has no environmental impact" is false.
"AI is destroying the planet" is also an oversimplification.
"AI has no impact on artists" is false.
"AI will inevitably replace all artists" is also not established.
The evidence suggests something much more complicated.
AI has real environmental costs.
It consumes electricity.
It can consume water.
It requires hardware and raw materials.
It contributes to electronic waste.
And its energy demand is growing quickly.
At the same time, AI is becoming much more energy efficient, its current share of global electricity consumption remains relatively small, and some AI applications could potentially help reduce resource consumption and emissions elsewhere.
The same applies to employment.
AI will automate certain tasks.
Some workers will be negatively affected.
Some jobs will change.
New workflows and potentially new jobs will also appear.
The final outcome is not predetermined.
- What should we actually be debating?
Instead of asking whether AI is simply "good" or "bad", I think the more useful questions are:
How can AI systems become more energy efficient?
How can data centers reduce their water consumption?
How can we increase the use of low-carbon electricity?
How can electronic waste be reduced?
How can AI companies become more transparent about their environmental impact?
How should creators be compensated and protected?
Which creative tasks should remain human?
Which tasks can reasonably be automated?
How can AI be used where it provides genuine value rather than unnecessary resource consumption?
These are much more useful questions than simply saying "AI is bad."
The point of this article is not to claim that AI is environmentally harmless.
It is not.
The point is that many claims about AI's environmental impact and its effect on artists are presented without enough context.
A scientific discussion should distinguish between measured data, modeled estimates, predictions and exaggerated social-media claims.
AI has real costs and real risks.
But that does not make AI inherently evil, nor does it mean that every person who uses AI is doing something environmentally irresponsible.
The most reasonable approach is to improve the technology, reduce its environmental footprint, protect people affected by automation, and use AI where it provides meaningful benefits.
The goal should not be to deny the problems.
The goal should be to understand them accurately.
Sources:
International Energy Agency - Energy and AI https://www.iea.org/reports/energy-and-ai
International Energy Agency - Key Questions on Energy and AI https://www.iea.org/reports/key-questions-on-energy-and-ai
United Nations Environment Programme - Artificial Intelligence: End-to-End Environmental Impact https://www.unep.org/resources/report/artificial-intelligence-ai-end-end-environmental-impact-full-ai-lifecycle-needs-be
Nature Sustainability - Environmental impact and net-zero pathways for sustainable artificial intelligence servers in the USA https://www.nature.com/articles/s41893-025-01681-y
Communications of the ACM - Making AI Less "Thirsty" https://doi.org/10.1145/3724499
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