Vertiv and GE Vernova poised to outperform through 2030 on AI data center power demand

The top five US hyperscalers are projecting a combined capital expenditure of $660 billion to $725 billion for 2026, nearly double their 2025 outlays, as the AI build-out shifts from software to physical infrastructure. Microsoft is guiding for roughly $175 billion in adjusted capital expenditure for both FY2026 and FY2027, with two-thirds of quarterly spend going to short-lived assets like CPUs and GPUs and the rest to long-lived data center infrastructure, and it added 1 gigawatt of capacity in Q3 FY2026, doubling its global footprint in two years. Amazon AWS has raised its 2026 capex guidance to approximately $220 billion, with CEO Andy Jassy saying AI capacity is expected to remain constrained through 2027 and contracted demand extending into 2028. Meta saw profit drop 14% in Q2 2026 despite a 28% revenue increase as its build-out, including a 1 gigawatt data center in Ohio and a Louisiana facility that could scale to 5 gigawatts, compressed margins, while Alphabet raised its 2026 capex guidance to as much as $205 billion and its Google Cloud backlog more than doubled year-over-year to $240 billion. The Stargate joint venture involving Oracle, OpenAI and others targets up to $500 billion in infrastructure investment by 2029, and Oracle's FY2026 capex reached $55.7 billion, more than doubling from the previous year.

Citi says growing political opposition to artificial intelligence infrastructure ahead of the November U.S. midterm elections has not materially weakened the data center construction pipeline. Data center development has become a bipartisan flashpoint, with local governments introducing moratoriums and at least 15 state legislatures proposing tighter regulatory restrictions, yet spending remains strong as AI infrastructure demand continues to support development. The impact has been concentrated among speculative and early-stage projects, which are increasingly delayed or cancelled during local approval processes, while late-stage developments that have already secured sites and grid connections continue to move ahead. Hyperscalers are seeking workarounds to power constraints and local restrictions, with Amazon pursuing direct investment in nuclear development with Dominion Energy and Meta securing a major nuclear power purchase agreement with Constellation Energy. Citi does not expect another market shock comparable to the emergence of DeepSeek, arguing investors have already adjusted to the prospect of highly efficient Chinese models, though it flags a potentially greater risk from governments restricting models deemed too dangerous, which could abruptly create excess computing capacity.

Nvidia, Google and Emerald AI have launched the AI Energy Management Alliance, or AEMA, a coalition that dynamically manages the electricity use of data centers in response to grid conditions. Emerald AI founder and CEO Varun Sivaram said the alliance's founding members are joined by a cohort of 20 launch partners, including the AI lab Anthropic, the semiconductor firm Analog Devices, and the energy companies AES, NRG, Constellation, RWE and National Grid. Sivaram said Emerald AI, which was founded under two years ago, is building with Nvidia and Digital Realty the world's first from-the-ground-up power-flexible AI data center, a 100 megawatt facility in Manassas, Virginia, that comes online later this year. He said Google, one of the founding members, has already done a gigawatt of demand response for its data centers, while Emerald and Nvidia have completed six demonstrations around the world, in London, Phoenix and Virginia. Sivaram said the alliance is talking to the FERC commissioners, state regulators and the administration about a grand bargain in which flexible AI data centers act as good citizens to grids and communities in return for faster and larger connections to the power grid.