A Roadmap for Sustainability in AI

It's time for AI companies to tackle their environmental and social challenges

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Hey there! 👋

Skander here!

If you've been following tech (or any) news lately, you've undoubtedly noticed we've entered the age of AI.

Having spent the last decade working at the intersection of Data & AI, I've seen firsthand how the focus has been on making AI "work" - finding sticky use cases and developing models that don't hallucinate.
But one crucial aspect has been largely overlooked: the impact of data centers and model training on our climate.

This has shifted in the last months: Now AI has become the hottest topic in climate circles. Every conversation I have with investors and utilities seems to circle back to AI these days.

Here's why:

To better understand AI’s growing energy use, analysts need a data revolution.

• Datacenters are using more and more energy.

• The Electric Power Research Institute predicts that data centers could consume 9% of U.S. power generation by 2030.

• Tech giants heavily investing in AI, like Microsoft and Google, are missing their climate goals.

• Utilities are witnessing demand spiking and struggling to find solutions.

And here's the kicker: when you look at AI companies, their sustainability strategies are mostly non existent.

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That's why we've brought in Tracy. With her background leading sustainability at AI company Cruise and over a decade of experience at the largest U.S. utility, she's uniquely positioned to tackle this critical issue.

In this deep dive, we're looking at:

• The current state of AI sustainability

• Challenges AI companies face in going green

• Finding comparables: How tech giants are benchmarking their sustainability efforts

• The economic upside of sustainable AI

• Solutions to rein in AI's carbon footprint

• A sustainability roadmap for AI companies

This is a tactical guide for AI companies who've been too busy disrupting industries to notice they might be disrupting the climate too.

🌊 Let's dive in

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But first, who is Tracy?

Tracy Cheung is a sustainability leader with over 15 years of experience in energy and advanced mobility programs. Her most recent role was Head of Sustainability at Cruise, a self-driving tech company, where she led initiatives to power the company's fleet with 100% renewable energy.

Tracy's background spans finance, utilities, and tech. She began her career in private equity before spending nearly 12 years at PG&E, the largest utility in the U.S., where she launched several distributed energy resource (DER) programs. At PG&E, she led projects such as redesigning energy billing statements and implementing home energy reports that resulted in significant household energy savings.

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Introduction

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How AI companies can address these problems

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Key Environmental and Social Challenges for AI Companies

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Finding comparables: Benchmarks within the Tech industry

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What AI companies’ carbon footprints look like

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Meta as a case study for AI companies’ future carbon footprint

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Recommended focus areas and ambition levels for AI companies

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Sample roadmaps

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Meta as an environmental case study - how AI companies could drive future impact

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Last but not least: A look into the future