Every year, US tech giants extract an estimated €19 billion from European economies through AI infrastructure - using European energy, land and resources while avoiding fair compensation. This invisible digital heist overshadows earlier concerns about AI's use of training data and intellectual property.
The mechanism is subtle but powerful: While providing valuable AI services to European businesses, US companies bundle these services with US-owned cloud infrastructure, creating a closed loop that captures value while bypassing European providers and tax systems.
Estimating the extracted value is hard, due to the lack of transparency and a strong practice of secrecy. However, taking a systems perspective can reveal the underlying extraction mechanisms and create a model to estimate the economic impact.
Overview of the systems-level view of money flow in AI services to infrastructure and resources. Source: Leitmotiv
The missed opportunity for Europe is twofold. First, European infrastructure providers are left out of the 19 billion market for AI infrastructure. Second, the profits from the provisioning of infrastructure are not taxed which represents an estimated 1.34 billion (using the average EU corporate tax rate of 21.5%) in missed tax revenue. Given that energy infrastructure, land and natural resources are used, a return for society through taxation should be the minimum.
In this brief, we will explore the mechanisms of resource extraction, direct value creation as well as the market barriers which prevent European infrastructure providers from competing. Furthermore, we will give policy recommendations on how to separate the practice of bundling services and infrastructure and enforce transparency on the flow of infrastructure resources (digital resources) in order for Europe to regain control over its digital economy & infrastructure.
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This entire paper and the background materials used for the calculation are available open-source. We welcome improvements and suggestions.
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To understand the flow of money, we take a hypothetical example of a large European enterprise with an annual IT budget of 100 million euros. To illustrate our example, we assume 1% of the budget is spent on purchasing AI services. For our example, we assume the enterprise is buying services from a US frontier model provider (such as Anthropic, OpenAI, Google, xAI, and others). All of the service providers operate using a legal entity in the US. Consequently, the 1 million in AI service spent is flowing to the US and becomes an import for Europe.
To deliver the AI service, the provider must install its model on computers with the capability to run them and enable the model to be queried (inference). These computers contain Graphical Processing Units (GPUs) which provide the necessary horsepower to offer fast inference for the customer. All Frontier service providers rent those computers from US cloud providers, bundling their models with the computing resources of the infrastructure provider. The reverse also happens, where a cloud provider does the bundling. This is the case with Anthropic’s Claude model, which is available within Amazon’s cloud platform as Amazon Bedrock.
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This is akin to an electric car manufacturer partnering with a utility and offering a car that is bundled with an electricity contract of the utility, locking customers into a single utility providing the electricity.
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An obvious question that comes to mind is: If the cost of computing is bundled with the model to provide the service, wouldn’t the model provider have an incentive to partner with infrastructure providers who offer the lowest price for the compute? This would increase the profit margin of the model provider and thus would make economic sense.
There are two straightforward reasons why this doesn’t happen: