World Model Readiness Whose cloud is your strategy on?

Module · Whose cloud is your strategy on?

The Data Sovereignty & Cloud Check

Every AI stack rents its foundations from someone else; the question is how much you would lose if that landlord changed the terms. Where your data and models actually run, whose courts govern the contract, and what it would cost to leave are usually left unexamined until a price hike or a policy shift forces the issue. This module checks the five pieces of that dependence honestly, before it is decided for you.

Question 1 of 5 · You know where it runs

Do you know exactly where your data and models physically run?

A region setting in a console is not the whole answer: subprocessors, caching layers, inference locations and vendor support access all move data across borders. If you cannot name the countries and companies involved, you cannot reason about sovereignty at all.

Question 2 of 5 · You could leave

If your main AI vendor doubled prices or vanished tomorrow, could you leave?

Exit is a capability you build in advance, not a decision you make in a crisis. Exported data in a portable format, a tested alternative, no fine-tuning locked in a proprietary shape. Most teams discover the true lock-in only the day they try to move.

Question 3 of 5 · Jurisdiction understood

Do you know which country's laws and courts govern your AI contracts and data?

The governing-law clause decides who can compel access to your data and where you go when things break. A US-jurisdiction contract can expose EU data to foreign legal reach regardless of where the servers sit. Read the clause before you need it, not after.

Question 4 of 5 · Alternatives evaluated

Have you honestly assessed whether a sovereign or EU-based alternative could do the job?

The reflex is that only the hyperscalers can serve your needs. Sometimes true, often simply untested. European and self-hostable options have narrowed the gap for many workloads; not evaluating them is a choice you are making, not a fact you have checked.

Question 5 of 5 · Switching cost honest

Do you have an honest number for what leaving your current stack would cost?

Switching cost is the real measure of dependence, and it is usually understated on purpose. Retraining, re-integration, data migration, staff relearning, all add up. An unquantified switching cost is a lock-in you have chosen not to look at.

For the statistics · one click each

Three questions for the public picture

These do not affect your score. They feed the anonymised, aggregated statistics; groups under 8 respondents are never shown.

Where does the AI infrastructure you depend on primarily run?

US hyperscaler
EU region of a US provider
European provider
Self-hosted
We do not know

How prepared are you to switch away from your main AI vendor?

Fully locked in
Very hard
Possible with effort
Exit-ready
No single vendor

Under which jurisdiction does your primary AI contract sit?

United States
EU or EEA
Elsewhere
Mixed across vendors
We do not know

Your context

Used to calibrate the report. Company size and sector remain in the anonymized dataset; your email does not.