The exponential growth of generative artificial intelligence (Gen AI) could derail global efforts to reduce carbon emissions, potentially consuming as much energy as entire countries, according to a new report from SAS. 

The report, ‘Rethinking data and AI in the cloud: How to move to a sustainable future,’ emphasised how senior decision-makers in large organisations are grappling with dual challenges: harnessing data and AI on an ever-increasing scale while urgently reducing carbon emissions.

To put the challenge into perspective, according to official figures, Ireland’s energy-hungry data centres consumed more electricity last year than all of its urban homes combined. In its report, SAS also suggests that if Google were to power its entire search engine operations using AI, it would require as much electricity as is needed to power the Republic of Ireland. 

Other experts have warned that the AI industry could consume the same energy as the Netherlands by 2027 unless growth slows.

Jerry Williams, chief environmental officer, SAS, said: “Organisations often think that environmental responsibility is primarily a cloud vendor obligation, but the truth is, it’s a shared responsibility.”

“Greater efficiency in AI model development, made possible by the availability of data and AI platforms that are optimised to run in the cloud, will also help teams to reduce unnecessary duplication and waste and minimise energy consumption.”

The report, drawing on insights from industry experts, highlights the growing problem of data consumption and its environmental impact. Cloud computing, while offering operational efficiencies, significantly contributes to carbon emissions. 

Innovations in data centre design and management by cloud hyperscalers like AWS, Microsoft Azure, and Google Cloud Platform are making strides in sustainability. Still, the responsibility extends to the organisations using these services.

To make matters worse, global emissions from cloud computing range from 2.5% to 3.7% of all global greenhouse gas emissions, exceeding those from commercial aviation. The report also sheds light on the inefficiencies in cloud proliferation. SAS research found that cloud and analytics sprawl is causing problems for 99% of large organisations, leading to increased infrastructure, storage, and processing costs and a hidden environmental impact. Optimising cloud environments is crucial for reducing both financial costs and carbon emissions.

In short, the widespread adoption of Gen AI tools threatens to exacerbate this issue, but as Luke Davies, MD of data centres at GlobalConnect, said: “Without data centres, there will be no AI – so there’s a structural incentive to make them as efficient as possible.”

SAS outlines five steps organisations can take to optimise their cloud infrastructure and improve energy efficiency:

1. Create a sustainability culture
2. Understand the environmental impact of computational workloads and make continuous improvements
3. Tackle cloud proliferation
4. Take a strategic approach to model development with a low/no/yes code platform
5. Choose the right partners

Irrespective of the numerous worries, SAS also underscored that decelerating the expansion of AI would be detrimental, possibly blunting advantages such as efficiency, productivity, and innovation. Furthermore, the report emphasises advancements in data centre architecture and administration that may assist in reducing the environmental consequences of growing AI usage. 

These encompass implementing more effective cooling methods and applying AI to enhance the efficiency of data centre operations. As the demand for AI and advanced analytics continues to grow, the report urges organisations to scrutinise and optimise all areas of their operation—including data and AI workloads—to avoid accusations of greenwashing and contribute meaningfully to global decarbonisation efforts.

See also: Generative AI is a top driver for cloud investments

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