Published On 7/7/2026
|
Last update: 14:47 (Mecca time)
The artificial intelligence revolution has always been associated with the idea of improving human lives, raising business efficiency, and helping to confront global challenges such as climate change, but behind this rapid technical development, there is an increasing environmental challenge represented by the rise in energy consumption and the increase in carbon emissions resulting from the operation of giant smart models.
As major technology companies expand the development of generative artificial intelligence, data centers and electronic chips have become a major part of the global emissions equation.
Read also
list of 2 itemsend of list
Emissions rise as artificial intelligence expands
Recent sustainability reports for Google and Amazon revealed a noticeable increase in their carbon emissions, coinciding with the expansion of their investments in artificial intelligence and cloud computing.
According to Google’s 2024 sustainability report, the company’s total emissions increased by approximately 13% during 2023 compared to the previous year, reaching about 14.3 million tons of carbon dioxide equivalent. The company attributed a large portion of the increase to higher energy consumption in data centers, in addition to emissions related to the supply chain.
As for Amazon, it announced in its 2023 sustainability report that its total emissions amounted to about 68.8 million tons of carbon dioxide equivalent, with an increase primarily related to the expansion of its logistics operations and cloud computing infrastructure through its arm, Amazon Web Services.
Data centers…the engine of artificial intelligence and the largest source of energy
Modern AI models such as Large Linguistic Models (LLM) rely on thousands of graphics processing units (GPUs) running for long periods of time during the training and running phases. These operations require huge amounts of electricity and require advanced cooling systems to prevent equipment from overheating.
The International Energy Agency (IEA) indicates that data centers consumed about 460 terawatt-hours of electricity globally in 2022, and this number is expected to double as artificial intelligence and cloud computing applications continue to grow over the coming years.
The environmental impact of data centers is not limited to electricity only, as many of them rely on large amounts of water for cooling systems, which raises additional concerns in areas that suffer from scarcity of water resources.
Indirect emissions…the biggest problem
Although technology companies invest billions of dollars in renewable energy, the bulk of their carbon footprint comes from what are known as Scope 3 emissions, which are emissions resulting from activities that the company does not directly control.
These emissions include server manufacturing, chip production, data center construction, equipment transportation, and use of products by customers.
In the case of artificial intelligence companies, the chip industry has become a key factor in rising emissions. The production of advanced graphics processing units requires complex manufacturing processes that consume large amounts of energy and water, in addition to the use of chemicals that have a strong effect on global warming.
According to the Semiconductor Industry Association, the semiconductor industry is an energy-intensive industry, as advanced factories require continuous operation and precise environmental systems to maintain production quality.
The AI race is bringing back dependence on fossil fuels
Although technology companies have pledged to rely on clean energy, the rapid increase in demand for electricity has prompted some companies to reconsider using traditional energy sources to ensure grid stability.
Technical reports indicate that major companies have begun to look for solutions such as nuclear energy or natural gas plants to provide stable power for data centers, especially with the rise in artificial intelligence needs.
This trend creates a challenge to carbon neutrality goals, because providing sufficient energy to operate artificial intelligence infrastructure may conflict with reducing dependence on fossil fuels.
Can artificial intelligence be made more sustainable?
Despite the challenges, technology and energy experts believe that artificial intelligence can become more environmentally efficient through a range of solutions, including:
- Develop smaller, more efficient AI models instead of always relying on giant models.
- Design of electronic chips with low power consumption.
- Improving the efficiency of data centers by using advanced cooling systems.
- Increase investment in renewable energy sources and electricity storage.
- Using AI itself to improve energy grids and reduce waste.
Companies such as Google confirm that artificial intelligence can help in many environmental areas, such as improving weather forecasts, managing electricity networks, and reducing energy consumption in buildings.
The future of the relationship between artificial intelligence and climate
Today’s artificial intelligence represents one of the biggest technological transformations in modern history, but it comes with a growing environmental cost. While this technology helps develop solutions to climate problems, the infrastructure needed to operate it raises energy demand and increases emissions.
The real challenge for major technology companies will not only be developing smarter artificial intelligence models, but rather building a technical system capable of growth without increasing pressure on the environment. Success in the age of artificial intelligence will not only be measured by the capabilities of machines, but also by the industry’s ability to achieve a balance between innovation and sustainability.
