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Escalating electricity needs from running AI data centers will create downstream investment benefits in the utilities, renewable energy generation, and industrial sectors, according to Goldman Sachs.
In a recently published study, equity analyst Carly Davenport has listed a basket of stocks positioned to benefit from the potential massive surge in U.S. power demand.
The investment bank forecasts that data center power demand will grow at 15% compound annual growth rate from 2023-2030. This growth trajectory is expected to elevate data centers’ share of total US power demand to 8% by 2030, up from the current level of approximately 3%.
The “U.S. power demand (is) likely to experience growth not seen in a generation. Not since the start of the century has US electricity demand grown 2.4% over an eight-year period, with US annual power generation over the last 20 years averaging less than 0.5% growth,” Goldman Sachs highlights.
Analysts estimate that about 47 GW of additional power generation capacity will be necessary to accommodate the growth in U.S. data center power demand by 2030. This demand is anticipated to be met by approximately 60% gas and 40% renewable sources.
The projection suggests that this trend will drive approximately $50 billion in capital investment in U.S. power generation capacity by 2030.
Goldman Sachs has pinpointed 16 stocks rated as “buy” across various sectors, including Utility, Clean Technology, Midstream, Energy Services, Industrials, and Industrial Tech.
The highlighted stocks are as follows:
AI Data Centers’ Demand Set To Triple By 2030: After experiencing relatively flat growth from 2015 to 2019, Goldman Sachs anticipates that power demand from data centers will more than triple by 2030 compared to 2020 levels.
According to analyst estimates, there is an upside scenario where demand could more than double the base case, influenced partly by improvements in product efficiencies and increased demand for AI-related technologies.
“There could be meaningful upside to our base case if appetite for purchase and utilization of servers is unconstrained,” Davenport stated.
“There could be downside to our base case if power efficiency is higher than expected or if power/compute speed efficiencies lead to fewer servers purchased than expected,” the analyst added.
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