AI’s Environmental Cost Sparks Procurement Challenges
The rapid growth AI is having a profound impact on public health and the environment, with new research highlighting the financial and social costs of AI-driven energy consumption.
A study by UC Riverside and Caltech estimates that pollution from data centres has led to more than US$5.4bn in healthcare expenses across the US over the past five years.
The rising cost of AI infrastructure
Data centres form the foundation of AI operations, consuming vast amounts of electricity - often from fossil fuel sources.
The resulting emissions have long been linked to respiratory diseases, cancer and other serious health conditions.
In 2023 alone, air pollution from data centres was responsible for approximately US$1.5bn in healthcare costs, a 20% increase from the previous year.
Google, Microsoft and Meta are identified as the biggest contributors, with Google accounting for US$2.6bn in health-related expenses over five years.
The demand for AI infrastructure is rising at an unprecedented rate.
By 2025, Microsoft, Google, Amazon and Meta are expected to invest a combined US$320bn in AI technology, more than double the US$151bn spent in 2023.
OpenAI and SoftBank have also announced plans to invest $500bn, bringing total AI-related spending from just six companies close to US$1tn.
The International Energy Agency warns that electricity consumption from data centres could double by 2026.
A single ChatGPT query already uses nearly ten times the electricity of a standard Google search.
Goldman Sachs estimates that by 2030, data centres could consume 10% of all US electricity, up from 4% in 2023.
Europe is also preparing for a surge in energy demand, with data centres expected to increase power consumption by 40 to 50% over the next decade.
This has already placed a strain on national grids, particularly in countries like Ireland, where data centres now use 21% of the country’s electricity - more than all urban households combined.
AI’s impact on Procurement and resource management
Beyond electricity, AI-driven infrastructure is placing increasing demands on water and electronic components. Data centres generate intense heat, requiring advanced cooling systems that rely heavily on water.
According to Google’s 2024 Environment Report, the company’s data centre water consumption has risen by nearly 88% since 2019. In water-scarce regions like California, this trend is worsening existing shortages and raising concerns about long-term sustainability.
Electronic waste (e-waste) is another growing challenge. AI chips and servers have a limited lifespan, and improper disposal of outdated hardware contributes to hazardous waste. Many components contain toxic materials, posing environmental and health risks. As AI infrastructure expands, procurement teams must factor in not only the initial costs of equipment but also the environmental and regulatory implications of its disposal.
The strain on supply chains is also becoming evident. The demand for advanced AI chips has surged, leading to global shortages and increased costs. Governments and corporations are now rethinking procurement strategies to ensure long-term availability of key components while minimising environmental damage.
Balancing growth with sustainability
The environmental burden of AI does not impact all communities equally. Data centres are often built in areas with cheaper land and lower regulatory requirements, such as West Virginia and Ohio. These regions, which tend to have lower-income populations, experience higher levels of air and water pollution as a result.
Shaolei Ren, Associate Professor at UC Riverside, explains: “Unlike carbon emissions, the health impacts caused by a data centre in one region cannot be offset by cleaner air elsewhere."
To mitigate their carbon footprint, tech companies are purchasing renewable energy credits, but critics argue that this approach does not address the direct environmental damage.
Sebastián Lehuedé, Assistant Professor at King’s College London, highlights the limitations of this strategy: “There are so many issues around carbon credits from an ecological perspective,”
“If you consume water somewhere to the point where it affects biodiversity in one area, that cannot be offset by having a nice project elsewhere.
“You’re going to cause irreversible damage if you keep to that logic.”
Some companies are taking steps to address these concerns.
Microsoft has signed an agreement with Constellation Energy to restart a nuclear power unit at Pennsylvania’s Three Mile Island, aiming to reduce reliance on fossil fuels.
“To achieve our goal of becoming carbon negative by 2030, we will need a broad range of innovative carbon-free energy solutions,” says Melanie Nakagawa, Chief Sustainability Officer at Microsoft.
“Advanced nuclear energy and fusion energy are included in our multi-technology approach to reaching this target.”
Other efforts include research into more energy-efficient AI models, improved cooling systems and sustainable procurement practices.
However, as AI development remains profit-driven, experts warn that sustainability may remain a secondary concern rather than a priority.
Public opposition to data centre expansion is growing, with protests emerging in the US, Ireland and Mexico over concerns about water shortages, pollution and rising energy costs.
Campaigners are demanding stricter regulations and increased accountability from the tech industry.
Revathi Kollegala, a Digital Strategist at CIFOR-ICRAF, warns: “We are going to reach a tipping point where the increasing cost of data and hence, AI, is not just environmentally expensive but also socially expensive,”
“This will undermine the logic that AI can democratise access to knowledge and reduce inequity.
“We may have reached that point already or will very soon."
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