Columbia Threadneedle: Power hungry AI - investment implications in the era of energy transition

At a glance

• The growth in AI and associated data centre expansion is set to increase power demand. This has significant implications in the era of energy transition.
• We explore options for power provision including behind the fence locations at nuclear and gas plants alongside efforts to improve grid connectivity and efficiency.
• Emissions will increase as a result of data centre expansion. Big tech will likely use some non-renewable resources but we expect them to continue investing in renewables.
• The AI revolution is thirsty for energy. We see numerous opportunities including quality names in areas like energy efficiency and provision of clean energy infrastructure.

Understanding the implications of AI growth

We have undertaken deep research and analysis on the investment implications of AI growth. The work has involved eleven analysts across our research platform and brought together experts on different industries and themes.

In this research we assess whether our semiconductor demand forecast through to 2028 can be met with an equal amount of data centre capacity. Within that framework we analysed the ability of the grid to meet power demands as well as considering non-grid options. We also explored the ability of industrial, machinery, and equipment suppliers to support growth of the AI ecosystem and looked at the impact of all this expansion on copper demand. And lastly, the impact on carbon emissions.

Here we focus on the implications of AI growth on power and the energy transition in the US. We find that meeting the high demands of AI will prove challenging but conclude with some confidence that between grid and non-grid options, these power demands can be met. However, we believe that some specific markets will not be able to generate adequate power, which will push AI demand to markets where power availability is greatest.

We anticipate higher demand than the consensus

The starting point of this analysis is our forecast for AI compute demand. Our predictions are materially higher than consensus and are driven by our FLOP/GPU estimates that see the AI Accelerator market potentially growing at 50% (compound annual growth rate) to $500B by 2028. As a result, our AI data centre energy demand forecast is also materially higher than consensus.

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