Morgan Stanley warns that U.S.AI infrastructure may face power, approval, and supply-demand risks

AT A GLANCE

Morgan Stanley says that U.S.AI infrastructure investment faces approval, supply-demand, and power risks, and could face a power shortfall of 2028 by 32 GW.

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Morgan Stanley warns 1600000000000 USD AI Infrastructure investment faces multiple risks: the U.S. could still face a power shortfall by 2028 32 GW

Dongcha Beating AI Breaking News: Morgan Stanley has summarized the core risks facing U.S.AI infrastructure development as “people, power, and politics.” It believes that tighter local-government approvals, a supply-demand reversal causing simultaneous declines in volumes and prices, and power shortages could jointly affect up to 1600000000000 USD of AI infrastructure investment plans.

Politically, data-center site selection, grid-connection applications, electricity-pricing mechanisms, and tax incentives are mainly influenced by state and local governments. As the U.S. midterm elections approach, restrictions on data-center construction could become an important factor affecting AI industry sentiment. The report notes that eliminating related tax incentives has become a bipartisan issue, while regulatory decisions by public utility commissions could also have a long-term impact on project implementation.

On supply and demand, Morgan Stanley warns that the current supply shortage of AI computing capacity is prompting companies to procure early and accept premiums. However, once supply catches up with demand or demand growth slows, upstream products such as chips and memory could face simultaneous declines in prices and shipments, putting pressure on margins. Even if cloud providers’ capital expenditure merely enters a plateau, it could weaken suppliers’ pricing power.

Power is the most immediate constraint at present. Morgan Stanley’s model shows that, even accounting for power-supply solutions such as nuclear energy, gas turbines, and fuel cells, the U.S. could still face a net power shortfall of 2028 by 32 GW, and the shortfall could widen to approximately 2029 by 72 GW. Delays in power delivery could prevent GPU procured by cloud providers from being put into use in time, resulting in equipment stockpiling and inventory backlogs.

Morgan Stanley currently maintains a constructive view on AI infrastructure, believing that power shortages are more likely to delay projects than cause demand to disappear entirely. However, the bank warns that if political resistance, power bottlenecks, and a supply-demand reversal overlap, they could hinder chip procurement, reduce upstream margins, and even reverse the entire AI capital-expenditure cycle.

Original link https://m.theblockbeats.info/flash/372791

Key points

Morgan Stanley summarizes the core risks facing U.S.AI infrastructure development as “people, power, and politics.”
The reported AI infrastructure investment plan is valued at up to 1600000000000 USD。
Morgan Stanley’s model shows that, even accounting for power-supply solutions such as nuclear energy, gas turbines, and fuel cells, the U.S. could still face a 2028 GW net power shortfall by 32.
The model believes that the power shortfall could widen to approximately 2029 by 72 GW.
Morgan Stanley still maintains a constructive view on AI infrastructure, believing that power shortages are more likely to delay projects than cause demand to disappear entirely.

AI-assisted interpretation

The following is analysis, separate from reported facts. Verify important claims independently.

This breaking-news item relays Morgan Stanley’s risk assessment: data-center construction could be affected by local approvals, grid connections, electricity prices, and tax policies; if computing-capacity supply catches up with demand or demand growth slows, chips and memory could simultaneously experience declines in prices and shipments; delays in power delivery could also prevent already procured GPU from being used in time.

Why it matters to readers

If these risks overlap, data-center commissioning and GPU deployment could be delayed, while upstream suppliers’ pricing power, shipments, and margins could also come under pressure, affecting the AI capital-expenditure cycle.

Beginners should distinguish between “forecast risks” and “events that have already occurred”: 32 GW, 72 GW, and impacts on investment are all model forecasts or conditional assessments relayed by the report; they do not mean that the shortfall or an industry reversal has already been confirmed.

Risks and unknowns

The evidence does not provide the original Morgan Stanley report, so its model assumptions and calculation methodology cannot be verified.
32 GW and approximately 72 GW are both forecast values; the actual shortfall remains uncertain.
How local approvals, grid connections, electricity-pricing mechanisms, and tax incentives will change in the future remains uncertain.
Whether supply catches up with demand, whether demand growth slows, and whether cloud providers’ capital expenditure enters a plateau have not been confirmed.

Morgan Stanley warns that U.S.AI infrastructure may face power, approval, and supply-demand risks

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