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Corporate Governance/ESG

Why AI’s Resource Footprint Needs to Be Addressed

For businesses and public services, generative AI provides the means to transform their operations, making them more efficient and effective. Yet its high resource consumption means developers and users must find ways of deploying it sustainably.

5 min readBy Megha Kumar
Briefing details
Corporate Governance/ESG
Outlet
The World Financial Review
Published
Updated
Reading time
5 min read
Author
Megha Kumar

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Why AI’s Resource Footprint Needs to Be Addressed
Cover image for Why AI’s Resource Footprint Needs to Be Addressed

Executive summary

Board briefing at a glance
Distilled for CISO, CTO, and board audiences.

Key takeaways

  • Businesses and public services should conduct an audit of the resources required to drive their AI systems.

Business impact

Water stress will become an acute problem for data centres and semiconductor manufacturing.

Recommendation

The use of renewable energy to power the AI revolution is critical for meeting climate goals but the process is slow and highly uneven.

M

Megha Kumar

CEO

Dr Megha Kumar is a reputed domain expert on geopolitics, AI and digital regulation.

LinkedIn15 published articles

Across economies and industries, AI can contribute enormously to achieving net zero targets. For instance, it can help utilities allocate resources more efficiently; reduce energy wastage in hard-to-green transportation industries such as shipping; and optimise irrigation in agriculture. But just as it could be a boon as business and industry take steps to lower their carbon footprints, there is a potential downside. 

Developing and deploying this technology is resource-intensive, contributing to carbon emissions regardless of how it is used. Large amounts of electricity and freshwater are used in the development and deployment of AI models, not least to cool servers in data centres.

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[Photo by Geoffrey Moffett on Unsplash]

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