Observed Signal · Nov 3, 2026 · Technical Release · Source: techcrunch · Impact: 4/5 · Sentiment: Negative
AI Data Centers Turn to Old Jet Engines for Fast Power
AI data center builders, facing years-long waits for grid connections and new gas turbines, are increasingly turning to converted jet engines to generate electricity quickly. These engines, pulled from retired aircraft and rebuilt to burn natural gas, can power a data center within 24 months, compared to seven years for a traditional grid hookup in regions like Northern Virginia. Companies like xAI and OpenAI have already deployed such units, with ProEnergy supplying converted GE engines. Crusoe, which builds AI data centers, ordered 13 units in April but abandoned a $1.25B deal for Boom Supersonic turbines in September. While offering speed, these engines are less efficient and more polluting, making them a short-term solution to the power bottleneck.
This article highlights the critical power bottleneck for AI data centers, which is a major infrastructure challenge for the AdTech industry that relies heavily on cloud and AI services. The use of converted jet engines as a temporary solution underscores the urgency and scale of the problem, which could lead to increased operational costs and delays for digital advertising platforms and martech solutions.
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Key Takeaways & Evidence Grounding
- AI data centers are using converted jet engines to generate electricity due to grid connection delays.
- Rystad Energy analyst says jet-powered units can have a data center running in 24 months.
- xAI installed eight converted jet-engine turbines from ProEnergy in Mississippi for its Colossus 2 data center.
- Crusoe ordered 13 converted units from ProEnergy in April 2026.
- Crusoe abandoned a $1.25 billion deal with Boom Supersonic for gas turbines in September 2026.
Connected Companies & Entities
5 Entities mapped“Microsoft pulled out as the anchor customer for Nscale's data center in Loughton, England, due to power delivery delays.”
“OpenAI followed Musk's lead with gas turbines at its first Stargate site in Abilene, Texas.”
“Crusoe, a Denver-based startup building AI data centers, is constructing the Abilene campus and ordered 13 converted units from ProEnergy in...”
“GE engines commonly found on Boeing jets are being converted for power generation.”
“Microsoft pulled out as the anchor customer for Nscale's data center due to power delivery delays.”
Ontology Mapping & Concepts
Related Market Signals & Shifts
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AI Labs Adopt Onsite Gas Power to Bypass Grid
SemiAnalysis examines how AI datacenter operators are increasingly deploying onsite gas generation to avoid multiyear grid interconnection delays. The report traces a rapid move from grid dependence to Bring Your Own Generation (BYOG) strategies—led by xAI’s truck‑mounted turbines—to enable faster time‑to‑power. It documents large orders (e.g., an OpenAI/Oracle 2.3 GW Texas plant), broad supplier participation (GE Vernova, Siemens Energy, Doosan Enerbility, Wärtsilä, Boom Supersonic, Bloom Energy, Caterpillar, and others), and three main generator families (aeroderivative/industrial gas turbines, reciprocating engines, and solid‑oxide fuel cells). The analysis covers tradeoffs—capex, lead times, ramp rates, redundancy/overbuild needs, permitting, supply‑chain bottlenecks (turbine blades/cores)—and emerging commercial models such as bridge power and Energy‑as‑a‑Service. The market is characterized by acute supplier booking, rising lead times, and material impacts on datacenter economics and deployment timelines.
Behind-the-Meter Power Challenges for Datacenters
SemiAnalysis reports that behind-the-meter (BTM) power generation for AI datacenters has become mainstream, with 75GW of firm orders tracked, 20GW ordered in Q2 2026 alone. Major deals include Microsoft's 5GW with Chevron and Crusoe, Google's 930MW aeroderivative turbines and 900MW Bloom fuel cells, and OpenAI's 1.4GW campus with Jenbacher engines. The report details six key challenges: contracts & bankability, permitting, fuel supply, equipment procurement, workforce, and electrical physics. It highlights permitting delays (e.g., Oracle's Project Jupiter) and the rise of Energy-as-a-Service vendors like VoltaGrid. The analysis emphasizes the shift towards reciprocating engines and fuel cells, and the growing importance of balance-of-plant equipment.
TU Wien Study: AI Data Centers Must Become Flexible Power Users
An international research team led by TU Wien has published a study in the journal Joule warning that the rapid expansion of AI data centers could lead to a resurgence of fossil fuel power plants unless data centers become flexible electricity consumers. The study recommends shifting AI training to times of abundant renewable energy, new contracts with guaranteed base power and curtailable additional power (at most 35 hours per year), and better data on data center power consumption. The team highlights that 39% of planned US gas power capacity by end of 2025 is meant for data centers, citing xAI's use of mobile gas turbines in Mississippi without proper permits. They propose binding agreements to protect local populations from grid expansion costs. This contrasts with Nvidia CEO Jensen Huang's statements that fossil fuels will be used more in the coming years. The article also mentions Meta's new Enterprise Platform, which sells AI models, agents, and compute, to diversify beyond advertising.
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