The ESG Cost of Meta, Google & Microsoft’s AI Investments

The rapid expansion of artificial intelligence is leaving an indelible mark on public health.

Research from UC Riverside and Caltech estimates that pollution from data centres has cost the US more than US$5.4bn in healthcare expenses over the past five years.

The energy consumption of AI - and the air pollution that follows - is not just a climate issue but an urgent public health emergency.

Data centres, the backbone of AI, require massive amounts of electricity to function.

A lot of the time, this power often comes from fossil fuels, which results in harmful greenhouse gas emissions. 

For years now, these kinds of emissions have been linked to respiratory diseases, cancer and other serious conditions.

According to the study by UC Riverside and Caltech, air pollution from data centres contributed to an estimated US$1.5bn in healthcare costs in 2023 alone, a 20% increase from the previous year.

The research names Google, Microsoft and Meta as the biggest contributors to these public health costs, with Google alone accounting for US$2.6bn over the five-year period.

AI’s hunger for energy is only increasing

Right now, we’re only at the very beginning of the AI era. And the AI boom shows no signs of slowing down.

In 2025, Microsoft, Google, Amazon and Meta are projected to spend a combined US$320bn on AI infrastructure, more than double the US$151bn spent in 2023.

OpenAI and SoftBank have also announced plans for a staggering US$500bn investment in AI development.

That’s almost one trillion dollars between just six companies.

So, what’s the outlook? The International Energy Agency has warned that data centre electricity consumption could double by 2026.

A single ChatGPT query, for example, consumes almost ten times the electricity of a standard Google search.

Goldman Sachs estimates that AI-driven energy demand could push data centres to consume 10% of all US electricity by 2030, up from 4% in 2023.

Europe is also bracing for a surge in power demand, with a projected increase of 40 to 50% over the next decade due in large part to data centre expansion.

This demand has already placed strain on power grids in a number of countries across the world.

In Ireland, for example, data centres now consume 21% of the nation’s electricity - that’s more than the energy consumption of all urban households in the country combined.

Beyond carbon: AI’s impact on water and waste

The environmental impact of AI and data centres extends far beyond carbon footprint.

Powering AI requires a lot of energy, which in turn creates a huge amount of heat. 

If data centres overheat, the technology ceases to function properly, so sophisticated water cooling systems are used to regulate temperatures in the facilities.

As demand for data centres has skyrocketed, so has their demand for water.

According to Google’s 2024 Environment Report, its data centre water consumption has increased by nearly 88% since 2019.

In drought-prone regions like California – where Google is based – this water demand is exacerbating existing shortages, raising concerns about long-term sustainability.

The disposal of data centre hardware (otherwise known as e-waste) is another big issue.

AI chips and servers have a limited lifespan and their improper disposal constitutes hazardous waste.

Many of the components of data centre hardware contain toxic materials, which can pose serious health risks.

The sheer scale of AI infrastructure means that addressing these issues is becoming more urgent with each passing year. 

A public health burden on low-income communities

The consequences of AI’s environmental impact are not felt equally.

Data centres are often located in regions with cheaper land and lower regulatory barriers, such as West Virginia and Ohio.

These areas tend to have lower-income populations, who bear the brunt of the resulting air and water pollution.

“Unlike carbon emissions, the health impacts caused by a data centre in one region cannot be offset by cleaner air elsewhere,” says Shaolei Ren, an Associate Professor at UC Riverside.

Tech companies are making an effort to offset their carbon emissions through renewable energy credits, but this fails to address the direct pollution affecting local communities.

The reliance on market-based instruments rather than actual reductions in fossil fuel use has been widely criticised by environmental experts.

“There are so many issues around carbon credits from an ecological perspective,” says Sebastián Lehuedé, an Assistant Professor at King’s College London.

“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.”

Finding a sustainable path forward

Other than carbon credits, what are big tech companies doing to mitigate the impact of their AI programmes and data centres?

Microsoft has signed an agreement with Constellation Energy to restart a nuclear power unit at Pennsylvania’s Three Mile Island, a move aimed at reducing 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 of Microsoft.

“Advanced nuclear energy and fusion energy are included in our multi-technology approach to reaching this target.”

Elsewhere, there is ongoing research into more efficient AI models, improved cooling systems and energy-saving computational methods.

However, as long as AI development remains primarily driven by profit, experts warn that sustainability may remain an afterthought rather than a priority.

Public protests against the expansion of data centres are becoming more common, from the US to Ireland and Mexico.

Concerns over water shortages, pollution and energy costs are fuelling local opposition, with campaigners demanding more oversight and accountability from the tech sector.

“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,” says Revathi Kollegala, a Digital Strategist at CIFOR-ICRAF.

“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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