AI Data Centers And The Airline Supply Chain, A 2030 Outlook

Published on Oct 28, 2025, 2:17 pm CDTUpdated on Oct 28, 2025, 2:19 pm CDT

7 min read

Artificial intelligence is colliding with commercial aviation in unexpected ways. AI data centers are turning to aeroderivative gas turbines, machines derived from aircraft engines, to secure fast, flexible power. That decision taps many of the same suppliers, materials, and even fuels that underpin the airline supply chain, which is already strained by new aircraft delays and engine shop backlogs. The result is a feedback loop that risks prolonging aircraft shortages, elevating maintenance costs, and slowing capacity growth, especially in the United States, through 2030. ^1,2,3,4

Executive Summary

U.S. power demand from AI is surging, and data center developers are ordering aeroderivative turbines that share lineage, materials, and service networks with airline engines. The turbine orderbook is stretching toward the decade's end, while commercial engine maintenance remains capacity-constrained. Together with lingering new-aircraft delivery delays, this dynamic threatens to keep U.S. seat growth below potential, nudge fares and lease rates higher, and slow the retirement of older, less efficient aircraft. For travelers, the effect will be felt first in reliability and schedule flexibility, then in price. ^3,4,10,11

Key Metrics Snapshot

Why it matters: Data centers could more than double global electricity use by 2030, with the United States responsible for nearly half of growth in advanced economies. ^3,4
Travel impact: Engine MRO demand peaks around 2026 and stays tight through decade's end, prolonging groundings and turn times. ¹⁰
What's next: Gas turbine order books are being reserved into 2028 and beyond, with manufacturers discussing deliveries out to 2030. ⁴
Cost signal: IATA and partners warn of an additional multi-billion-dollar cost burden for airlines in 2025 from supply chain frictions. ¹²
U.S. lens: U.S. electricity consumption is projected to hit records in 2025 and 2026, driven in part by data centers, reinforcing the turbine rush. ¹³

Background

Commercial passenger aviation entered 2025 with deep order backlogs at Airbus and Boeing, limited by parts shortages and ongoing engine issues. The Pratt & Whitney powder-metal defect forced accelerated inspections and groundings across hundreds of A320neo-family aircraft, just as engine shops were grappling with labor and parts constraints. Turnaround times for new-generation engines are far above pre-pandemic norms, and consulting analyses indicate the tightness will persist through the decade. ^8,9,10

Data And Analysis

Trend 1, AI Power Demand Is Pulling On Turbines

AI-optimized data centers are on track to more than double global electricity consumption by 2030, with U.S. sites a dominant driver. Developers are responding with a wave of new gas-fired capacity and, crucially, with mobile or modular aeroderivative turbines that can be installed in weeks and started in minutes. Manufacturers report customers reserving slots years in advance, and one U.S. utility deal envisions multi-gigawatt builds into the early 2030s. For hyperscalers, turbine mobility and fast start capability are strategic, letting them bridge slow grid connections and load-follow volatile compute. ^3,4,14

A flagship example is GE Vernova's LM2500XPRESS program with Crusoe, an AI infrastructure developer building a large Texas campus that supplies OpenAI and other partners. The deal covers 29 aeroderivative units, approaching a gigawatt of flexible power. These orders illustrate how AI demand has moved beyond diesel backup gensets toward jet-engine-derived machines at scale. ^5,6

Trend 2, Shared Technology, Materials, And Suppliers

Aeroderivative turbines are, by design, derivatives of aircraft engines. GE's LM6000 traces directly to the CF6-80C2 core, and the LM2500 family uses similar architectures and hot-section concepts optimized for rapid start, high power density, and multi-fuel operation. That kinship implies overlapping supplier bases for superalloy blades and vanes, combustors, and specialized coatings. As the installed base of power turbines grows, replacement demand for hot parts accelerates, which turbine OEMs acknowledge could become a bottleneck without capacity expansion. Every increment of hot-section casting capacity or powder-metal throughput that shifts toward stationary turbines is capacity that cannot simultaneously service aviation peaks. ^1,2,7

The overlap extends into the secondary market. Industrial packagers refurbish or repurpose cores from legacy airframes, and airlines themselves have increasingly harvested engines and modules to cover spares gaps. That competition makes the pool of serviceable cores and life-limited parts tighter and more expensive, a dynamic acutely felt by carriers waiting on shop visits or deferred new-build deliveries. ⁹

Trend 3, Fuel And Logistics Converge

Most commercial jets burn Jet A or Jet A-1, kerosene-grade fuels. Aeroderivative turbines can run on a wide range of fuels, including natural gas, diesel, and kerosene-range liquids, and many packages are dual-fuel. In practice, U.S. data centers are prioritizing pipeline gas, but projects have capacity to switch to liquid distillates if needed. That flexibility means AI sites and airlines can, at the margin, draw on overlapping supply chains for kerosene-range molecules, delivery logistics, and emissions control consumables. Meanwhile, the broader rise in data center electricity demand is already pushing U.S. power consumption to records in 2025 and 2026, reinforcing developers' tilt toward gas-fired solutions and keeping distillate backup markets tight. ^2,3,13,15

Trend 4, Transmission To Airline Outcomes

On the aviation side, two constraints dominate the medium term. First, engine MRO capacity is structurally tight, with turnaround times elevated and a demand peak around 2026 that eases only gradually thereafter. Second, new aircraft output remains below unconstrained demand, despite large backlogs and aggressive production targets. When stationary-turbine demand competes for the same high-value hot-section supply and test-cell talent, it adds friction to both constraints. The result is slower restoration of airline spare-engine pools, higher green-time lease costs, and delays to planned fleet growth. U.S. carriers feel this fastest because domestic networks depend heavily on single-aisle fleets, precisely where engine shop queues and delivery delays are most acute. ^10,11

There are also local siting frictions. In several U.S. communities, large turbine farms aimed at powering data centers have triggered legal and permitting challenges, which can redirect local gas and equipment logistics and indirectly influence energy prices faced by airports and maintenance bases. These are not the primary drivers of airline costs, but they compound regional tightness. ⁵

Implications For Travelers

For U.S. travelers, the immediate effect is subtle but cumulative. Airlines will keep older aircraft longer to bridge delayed deliveries and slow shop cycles, which can dampen schedule flexibility and on-time performance if spares are thin. Network planners will prioritize profitable hubs and trunk routes, with thinner secondary routes gaining capacity later in the cycle. Globally, similar bottlenecks in Europe and Asia reduce widebody availability for long-haul links, which in turn tightens connection options for U.S. passengers and sustains yield pressure on transatlantic and transpacific fares in peak seasons. ^8,10,11

Final Thoughts

The through-2030 airline supply chain picture is a race between incremental capacity adds and new sources of demand. AI has made aeroderivative turbines strategic assets, and their lineage ties them to aviation's most constrained parts of the value chain. Unless engine MRO capacity, hot-section manufacturing, and new-aircraft output scale faster than current trajectories, the airline supply chain will remain tight, especially in the United States. For aviation leaders planning fleets, schedules, and budgets, treating AI-driven power markets as a core variable is now part of the airline supply chain playbook. ^3,4,10,11