Artificial intelligence (AI) has been presented by its supporters as the great promise of the 21st century, capable of revolutionising industries – and even helping in the fight against climate change. It is said, for example, that AI will optimise the integration of solar and wind power into “smart grids”, helping to reduce dependence on fossil fuels.
But the other side of this coin is not insignificant: the data centres that provide the computing power to train, deploy and run AI models are energy-greedy, and also generate emissions associated with their operations. The question is inevitable: in the fight against climate change, do the benefits of AI outweigh its negative impact?
Low share of power use today, but with future uncertainty
The data centres that support AI and other digital services consume huge amounts of energy. On a global scale, this currently only accounts for about 1% of electricity demand. But what happens as AI continues to expand? And what could go wrong?
Optimistic scenarios predict that advancements in the energy efficiency associated with software and hardware will keep explosive growth in power demand at bay. One example of this is the world’s largest AI chipmaker Nvidia, which claims that its new Blackwell system, a processor supporting generative AI, is up to 25 times more energy efficient compared to previous models – though, for all its gains in efficiency, each processor may still use significantly more power than its predecessors, drawing up to 1,200 watts per unit.
Other scenarios argue that the sophistication of AI models will come with exponential power consumption: generative AI developed on the basis of large language models (LLM) requires up to 30 times more power during the training phase than a traditional AI model. It is for this reason that a ChatGPT query has been estimated to use up to 10 times more electricity than a Google search.
Investments and risks on the rise
Increasingly complex and intensive uses of AI, such as video creation from text prompts, will require “hyperscale” data centres with power demands of more than 100 megawatts, potentially consuming the equivalent amount of electricity needed to power as many as 400,000 electric vehicles each year. Big technology firms have been duly gearing up: the IEA reports that in 2023, Google, Amazon and Microsoft together made capital investments that were greater than the entire US oil and gas industry – equivalent to 0.5% of the country’s GDP.
The accelerated evolution of AI means that its electricity consumption must be considered at least as a non-negligible risk in the coming years. There are already countries facing strain from the sector’s growth, such as Ireland, where data centres already accounted for over 20% of electricity consumption in 2023, putting pressure on the grid and triggering a moratorium on new data centres in Dublin until 2028.
The emissions paradox and hidden environmental costs
Paradoxically, AI and its voracious appetite for electricity is growing faster than the transition to fully renewable energy sources and systems. This not only perpetuates the technology’s dependence on fossil fuels, but has in some locations delayed the closure of coal-fired power plants, meaning increased greenhouse gas emissions.
In addition, data centres require large amounts of water for cooling, and critical minerals for the manufacture of their hardware, exacerbating problems of water scarcity and dependence on environmentally questionable supply chains.
The data also reveals a lack of transparency: in 2024, Microsoft and Google not only missed their climate targets, but the emissions associated with their data centres may be underestimated. According to studies, emissions from in-house data centres may be 7.62 times higher than what companies claim.
What about Latin America?
Analysts have highlighted Brazil, Mexico, Chile, Colombia, Peru, Uruguay, Costa Rica and Panama as the countries in Latin America with the highest growth and potential in terms of AI infrastructure. The region, together with Africa and the Middle East, accounts for 5% of the total global electricity consumption by data centres. This brings with it opportunities to strengthen connectivity, foster employment in technology and leverage investments in data centres to boost the integration of renewable energy into the region’s electricity matrix.
We need a strategy to avoid the emergence of a ‘digital extractivism’ that puts data centres at the exclusive service of industrialised countries, at the expense of ecosystemsFelipe Arango García
Indeed, the region is already seeing significant growth in the sector, with countries such as Brazil, Mexico and Chile attracting investors for their robust infrastructure, energy systems and permissive government policies. However, data centres are already putting pressure on electricity and water systems in Mexico, Chile and Uruguay – countries that already suffer from considerable water stress.
Furthermore, it will be necessary to develop a strategy for the harnessing of AI between countries of the Global South, and for its associated infrastructure, to avoid the emergence of a “digital extractivism” that puts data centres at the exclusive service of industrialised countries, at the expense of ecosystems.
The way forward
AI promises climate solutions, but its growing energy demand and environmental impacts create uncertainty. Without measures to ensure efficiency, transparency and sustainability, its development could deepen the crisis it seeks to solve. Latin America has a strategic opportunity, but it must avoid falling into a digital extractivism that aggravates inequalities and puts further pressure on its natural resources.
For this reason, it is essential that Latin American states engage in an open and frank dialogue with academia, the technology industry, think-tanks, and other countries in the Global South, to structure a value chain around the use of AI for the reindustrialisation of our region within the framework of a just energy transition. This involves developing policies, regulations, incentives and safeguards that channel AI towards a use focused both on climate adaptation and mitigation solutions, as well as on economic diversification and tax revenue generation solutions that favour emancipation from fossil fuels.
