AI Building vs. AI Buying: The Transatlantic Split

About the Author

Torsten Slok

Partner, Chief Economist

The US and Europe have fundamentally different roles in the AI economy. One is building it, and the other is using it. The US dominates on every supply-side measure: hyperscaler capex approaching $800 billion in 2026, data center capacity three times that of Europe and the dominant share of global AI models and semiconductor value, see the first three charts below.

Yet on adoption, several European countries are actually ahead of the US, and many European firms are using AI in their businesses (see the fourth and fifth charts). This suggests Europe is an eager user of infrastructure it did not build and cannot easily replicate.

The bottom line is that the US is the dominant AI builder, but both the US and Europe are AI adopters. For more, see our new chart book: The macro implications of the AI investment boom: US and Europe

Written by Huw van Steenis

Hyperscaler capital expenditure is expected to scale further from here — Sources: Factset, Apollo European and Policy Strategist, Apollo Chief Economist

Data center installed capacity 3x in US than Europe — Sources: IEA, Apollo European and Policy Strategist, Apollo Chief Economist

Only one model from Europe — Sources: AI Model & API Providers Analysis | Artificial Analysis, Apollo European and Policy Strategist, Apollo Chief Economist

Several European countries ahead of the US on AI consumer adoption — Note: AI diffusion is measured as the share of people between ages of 15 and 64 who have used a generative AI product. This measure is derived from aggregated and anonymized Microsoft telemetry and adjusted to reflect differences in OS and device-market share, internet penetration and country population. Sources: Global AI Diffusion in Q1 2026 - AI Economy Institute | Microsoft, Apollo European and Policy Strategist, Apollo Chief Economist

AI adoption by enterprises — Note: Survey reports the share of firms using at least one of eight specified AI technologies: 1) text mining, 2) speech recognition, 3) natural language generation, 4) image recognition and processing, 5) machine learning for data analysis, 6) AI based software robotic process automation, 7) autonomous robots or drones, self-driving vehicles, 8) generating pictures, videos, sound/audio. Sources: Eurostat 2025 EU-ICT-Firm Survey, Apollo European and Policy Strategist, Apollo Chief Economist

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AI Building vs. AI Buying: The Transatlantic Split

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