The Price of a Token I - Economical Perspective

AIGIS officially went live on 1 October.
For our first public post, we therefore deliberately chose not to begin with a product presentation or a list of features, but with a question we consider more fundamental: under what economic conditions can AI be produced and operated sustainably in Germany at all?

With "The Price of a Token – Study I: Economic Perspective", we are publishing the first AIGIS Research Study. Its starting point is the observation that the debate about AI costs is often reduced to individual factors: electricity prices, regulation, skilled labour, capital, infrastructure or cloud costs. In reality, however, these factors do not act independently of one another. Only in combination do they produce a reliable picture of the actual cost structure of AI production.

The study therefore treats the token not merely as a technical or billable unit, but as the result of a physical and organisational value chain. Energy, water and cooling, hardware and depreciation, buildings and network infrastructure, personnel, financing, regulation, utilisation and location conditions are considered together and related to the different operating models: On-Premises, Online and Hybrid.
This consolidated view is particularly relevant for Germany. Its location conditions are not problematic because of any single factor. What matters is rather that several disadvantages can overlap and reinforce one another. High running costs, tied-up capital, regulatory and administrative friction, infrastructure issues and limited scaling options affect smaller and younger market participants in particular more severely than large, internationally positioned companies.

This results in an economically relevant shift: AI can be used intensively in Germany while a growing share of its physical production base is built outside Germany. Compute capacity is built where energy, capital, infrastructure and regulatory conditions are more favourable. The AI output generated there is then imported into Germany via cloud services, APIs or other compute models.

As a result, productivity can arise domestically while a substantial share of the underlying investment, infrastructure, technical value creation and know-how is tied to other locations. It is precisely this separation between AI use and AI production that is a central subject of the study.
The same logic also helps explain why investors, start-ups and skilled workers are increasingly turning to locations where growth, compute availability and access to capital fit together better. The study explicitly does not claim a simple causality. Rather, it attempts to bring the various influencing factors together and make visible the conditions under which migration, relocation and growing import dependency become plausible.

Our approach here is deliberately sober: Evidence before assertion. Where reliable data is available, it is used. Where assumptions have to be made, they are marked as such. Where the data does not allow a conclusive statement, the result remains open.
This publication also marks the start of the AIGIS Research Series. Study I – Economic Perspective is the first building block of a series in which we intend to examine the economic, regulatory, ecological, social and strategic conditions of AI value creation both separately and in context.

The attached teaser shows the main cost drivers in condensed form. The full study will be made available on AIGIS.one and can be downloaded there after registration.

AIGIS has been live since 1 October. Our first official post is therefore not meant to explain what our product can do, but to show how we view AI: not as an isolated technology, but as a value creation system whose real conditions must be understood, analysed and made transparent.