The rapid adoption of data-hungry technologies, such as GenAI, poses a significant threat to decarbonisation initiatives unless organisations take greater responsibility for their cloud and data practices, experts have warned in a report by global data and AI organisation, SAS.

Senior decision-makers in larger organisations face the dual challenge of leveraging data and AI at an increasing scale while urgently needing to reduce carbon emissions.

This is a conundrum for leaders as they navigate the ethical, commercial, and regulatory imperatives to mitigate climate change. To put the challenge into perspective, Ireland’s energy-hungry data centres consumed more electricity last year than all of its urban homes combined, according to official figures.

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

“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, is a significant contributor 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, but the responsibility extends to the organisations using these services.

“If you reduce the time needed to run analytical workloads, it will also have the added benefit of significantly reducing your carbon emissions,” explains Spiros Potamitis, senior data scientist, SAS.

“However, what’s really important is that organisations see this as a shared responsibility. If all organisations have accountability for their computation efficiency in the cloud and for employing responsible ‘cloud citizen’ practices, the cumulative effect will be significant.”

The rise of GenAI further complicates the sustainability challenge. Reports indicate that models like ChatGPT-3 consume substantial resources, with ChatGPT-4 requiring even more.

Recent research from Morgan Stanley shows that the rise in data centre usage, driven by the AI boom, is expected to produce about 2.5 billion metric tonnes of carbon dioxide-equivalent emissions globally through the end of the decade.

As data centres are resource-intensive both directly, in terms of energy and water consumption, and indirectly, through construction and equipment use, the experts agree that the tech industry must innovate to meet sustainably demands.

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Potamitis stressed the need for organisations to use monitoring tools to understand their usage, build holistic ESG dashboards, and partner with sustainable software and cloud vendors. “It’s about making small, incremental changes that collectively have a significant impact. Even small improvements in cloud usage can make a big difference when considering the cumulative impact,” he said.

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, as well as a hidden environmental impact.

Optimising cloud environments is crucial for reducing both financial costs and carbon emissions.

As the demand for AI and advanced analytics grows, the industry must balance innovation with sustainability.

The tech sector is responding with innovations in data centre management and more efficient algorithms.

“The urgency of climate change, public pressure, and new regulations mean that businesses are increasingly prioritising sustainability when choosing providers,” Luke Davies, managing director of data centers at GlobalConnect said. “Without data centres, there will be no AI, so there’s a structural incentive to make them as efficient as possible.”

Potamitis concluded: “Given the urgency of climate change, organisations must go all in, hosting data with responsible service providers and continuously optimising their resources to reduce their emissions footprint.”