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Thought of the day

Mega-cap technology companies are scaling up their AI and cloud-computing capacity. Demand is also rising for the advanced data centers that host these complex, networked systems. All the above requires energy, including a continuous power supply and water-intensive cooling systems.

The International Energy Agency (IEA) estimates a single ChatGPT search requires nearly 10 times the energy of a traditional Google search query. And energy intensity may grow as AI data centers become increasingly large. Microsoft CTO Kevin Scott last month said: “We are nowhere near the point of diminishing marginal returns on how powerful we can make AI models as we increase the scale of compute.”

Growing numbers of tech companies are investing in new, nearby power infrastructure to satisfy their energy needs. Just one example is Google’s 115 megawatt (MW) power supply deal with NV energy and Fervo Energy in Nevada this week.

But, we argue that the AI cycle—while power-intensive—is not necessarily at odds with climate and decarbonization targets.

Mega-cap tech AI demand will need considerable renewable power. We expect the AI market to be dominated by an oligopoly of vertically integrated mega-cap tech companies with sufficient capital and cloud computing resources to compete. Meta, Google, Apple, Microsoft, and Amazon have all committed to sourcing 100% clean power, and together accounted for more than two-thirds of global corporate power purchase agreements (PPAs) in March, according to data from BloombergNEF. Maintaining this 100% clean power pledge will mean their renewable power demand growth will likely continue to outstrip utility-scale supply growth over the medium term, most notably in the US. Google’s Nevada power supply deal this week, while relatively small in scale, is built around carbon-free geothermal power.

Renewable energy storage is on the rise. US renewable capacity is growing rapidly, with a record 11GW of solar panels added in the first quarter of this year, according to SEIA/Wood Mackenzie estimates. Battery storage is a key element of this, helping to store power and offset the intermittent nature of solar and wind generation. The US Energy Information Administration (EIA) estimates US battery capacity will nearly double this year above 40GW. For the first time, battery storage was the top power source provider in California for several days last month. While this additional energy demand strengthens the thesis for solar and batteries, gaps in storage capacity and a geographic mismatch in the energy mix near data centers means natural gas is also likely to be part of the solution set.

We think higher emissions from AI data center construction are a temporary phenomenon. Building data centers with polluting materials like steel and cement boosts emissions in the short term, making it a meaningful concern. But the increase in emissions from data center construction should be temporary, and may incentivize faster innovation and adoption of green solutions that can increase circularity in the sector. For example, Microsoft says it will reuse 90% of its servers and components within its regional data center network by 2025, cutting down its reliance on virgin raw materials.

So, while explosive AI demand may drive rapid energy demand growth, we don’t see this impeding progress on decarbonization or the energy transition. What's more, we anticipate advanced AI models and inference queries that come out of some of these data centers will be key enablers of environmental and social solutions that can track, measure, and reduce greenhouse gas emissions.

We are also seeing increasing evidence that investor pressure via ESG engagement can be an effective tool in accelerating decarbonization. We therefore suggest investors factor in individual company greenhouse gas emissions when allocating capital to AI-related technologies or business models. With key greentech building blocks like solar, wind, and batteries increasingly mature, we believe the majority of our current power generation and transportation-related emissions can actually be eliminated with technologies already existing today.

The opportunities from AI and climate can also be captured through broader thematic investments, like"Clean air and carbon reduction," "Energy efficiency," "Water scarcity," and the "Circular economy."