Stay on the right side of the EU AI Act and the new wave of AI rules, without a six-figure legal bill.
You start from the real exposure: fines reaching €35M or 7% of global turnover for prohibited practices and €15M or 3% for high-risk failures, weighed against the cost of a lean in-house program. You'll see why disciplined, early compliance is far cheaper than reactive legal firefighting.
Your problem isn't missing knowledge. You already know the penalty exposure — up to €35M or 7% of total worldwide annual turnover for prohibited practices, and €15M or 3% for many high-risk and other obligation failures under Article 99 of Regulation (EU) 2024/1689. What you need is a way to act on it.
You read the headline "high-risk rules apply 2 August 2026" and assume there's nothing to do until then. But by the time those obligations bite, three earlier waves of duty have already been enforceable for months — and one of them is the prohibition.
You licensed a foundation model. You didn't train it, you can't see its training corpus, and you have no realistic way to audit the trillions of tokens that shaped it.
The cost objection usually arrives disguised as a question: "What's our compliance budget?" Behind it sits the assumption that conformity with Regulation (EU) 2024/1689 demands a standing legal department, a Big Four readiness assessment, and a six-figure retainer.
You've built one program against one regulation. Then a sales lead lands in São Paulo, a hiring tool goes live in Colorado, and your model starts answering prompts from users in Seoul.
Take an honest baseline first. Score each item from 0 (absent) to 3 (operational and evidenced). Inventory — do you have a current list of every AI system you build or deploy that touches the EU? Classification — for each, do you know its risk tier under the Act and why? Ownership.
Consider any organization that has quietly embedded a general-purpose model into a customer-facing decision: credit pre-screening, candidate ranking, eligibility triage.
This is the foundational artifact for everything that follows — spend an afternoon, not a fortnight. For every AI system you build, embed, license, or resell, capture one row: system name and one-line function (what it infers and what decision its output shapes), and whether it's in scope under the AI-system definition.
Consider a single high-risk creditworthiness model — a category Annex III covers for systems used to evaluate creditworthiness or establish credit scores — and how the same software generates four different obligation sets depending on who is holding it.
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