Oxford Economics: US Corporate High-Tech Spending to Rise 40% by 2027, Tripling Europe's Pace

A new macroeconomic forecast from Oxford Economics, reported by the Financial Times, projects that United States corporate capital expenditure on equipment, computing facilities, and structures will surge 40% between 2021 and 2027. This expansion rate is more than three times faster than equivalent capital investment across European economies over the same six-year window, driven primarily by private and hyperscaler investments in artificial intelligence infrastructure. The divergence underscor

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Oxford Economics: US Corporate High-Tech Spending to Rise 40% by 2027, Tripling Europe's Pace

A new macroeconomic forecast from Oxford Economics, reported by the Financial Times, projects that United States corporate capital expenditure on equipment, computing facilities, and structures will surge 40% between 2021 and 2027. This expansion rate is more than three times faster than equivalent capital investment across European economies over the same six-year window, driven primarily by private and hyperscaler investments in artificial intelligence infrastructure.

The divergence underscores a widening structural divide in compute deployment, data center construction, and enterprise technology adoption between the two economic regions.

Infrastructure Acceleration and Hyperscaler Outlays

According to the analysis, US business investment resilience has been anchored by massive high-tech equipment procurement, custom accelerator deployments, and specialized data center construction. While broader manufacturing and industrial equipment sectors have experienced cyclical softening, AI-related capital expenditure has outpaced historical baseline trends.

In the US, hyperscalers and frontier research labs are committing tens of billions of dollars annually to high-bandwidth memory (HBM), advanced packaging silicon, multi-gigawatt power interconnection agreements, and dense server clusters. Oxford Economics forecasts that enterprise technology spending directed specifically toward AI hardware, networking, and cloud services will expand from $340 billion globally in 2025 toward approximately $3 trillion by 2035, with American firms capturing the majority of initial deployment value.

Transatlantic Capital Expenditure Schematic

The European Investment Gap

In contrast, European corporate investment in advanced computing facilities remains constrained by several compounding structural bottlenecks:

  1. Power and Utility Costs: Industrial electricity prices across major European hubs routinely reach two to three times the rates available in key US compute corridors, complicating the unit economics of 100MW+ data center projects.
  2. Capital Formation and Debt Markets: US hyperscalers and AI infrastructure startups have tapped deep corporate debt markets, issuing over $220 billion in bonds throughout 2026 alone to fund multi-year GPU clusters, whereas European capital markets have generated far fewer multi-billion-dollar private infrastructure vehicles.
  3. Regulatory and Grid Timelines: Lengthy permitting intervals for transmission line buildouts and environmental compliance across EU member states continue to extend project delivery schedules relative to US and Asian developments.

Although the European Commission has established initiatives such as the €10 billion AI Gigafactories framework to stimulate domestic infrastructure, public funding pledges have yet to match the scale of private US balance-sheet allocations.

Transatlantic Productivity Trajectories

The widening gap in physical compute assets mirrors the macroeconomic divergence observed during the 1990s information and communication technology (ICT) boom. Historical studies from the Federal Reserve and Brookings Institution indicate that higher US investment in computing hardware and business software during that era generated a sustained productivity advantage, with US output per hour rising 88% between 1995 and 2025 compared to 30% across euro-area economies.

Oxford Economics notes that because frontier AI models require continuous hardware refreshes and specialized cluster co-location, firms located in ecosystems with immediate access to dense compute grids and low-latency API infrastructure are positioned to automate workflows and deploy agentic pipelines faster than peers in capital-constrained markets.


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