The Day the AI Act Grew Teeth: GPAI Enforcement Goes Live

Read Time: 13 minutes TL;DR On August 2, 2026, the part of the EU AI Act everyone was quietly ignoring became enforceable: the AI Office can now fine providers of general-purpose AI models up to 3% of global annual turnover or €15 million, whichever is higher, and can demand your technical documentation, run its own evaluations of your model, order you to “take measures,” and in the worst case make you restrict, withdraw, or recall the model from the EU market. The obligations themselves have technically existed since August 2, 2025 — technical documentation, downstream transparency, a copyright policy that honors robots.txt and opt-outs, a public summary of training data — but until now they were rules without a referee. That changed. Models judged to carry systemic risk (trained above 10^25 FLOP) carry heavier duties that read like a security checklist written by a regulator: model evaluations, adversarial testing / red-teaming, a safety-and-security framework, serious-incident reporting to the AI Office, and cybersecurity protection of the model weights themselves. The voluntary Code of Practice buys you a lighter touch, not immunity. Models already on the market before August 2, 2025 get until August 2, 2027 to fall in line. This is the regulatory half of a two-part story — the civil-liability half, the new Product Liability Directive, is the post I’m publishing right after this one. Read together, the EU has built a pincer: a regulator that fines you, and a courtroom that bills you. Here’s my security-practitioner read of the regulatory jaw. The dates that matter: Date What happens Aug 1, 2024 The AI Act enters into force Aug 2, 2025 GPAI model obligations begin (for models placed on the market after this date) Aug 2, 2026 Enforcement switches on — the AI Office / Commission can investigate, evaluate, order measures, and fine Aug 2, 2027 Compliance deadline for GPAI models already on the market before Aug 2, 2025 The usual disclaimer, same as always: I am not a lawyer, and this is not legal advice — it’s a security practitioner reading a regulation the way I read an attack surface, looking for where the pressure actually lands and who ends up holding it. If you build or ship AI models into the EU, talk to actual counsel. What I can tell you is what this changes operationally for the people who build, secure, and deploy these models — because buried under the compliance language is a list of things I have been demanding on this blog for two years, now backed by a fine. A note on framing before we start. This post is one of a pair. The EU is putting teeth behind AI on two different tracks at once, and they bite in different ways. This one — the AI Act’s rules for general-purpose AI — is regulatory: a public authority, the AI Office, with the power to investigate you and fine you. The companion piece, on the new Product Liability Directive, is civil: private plaintiffs and courts, strict liability, damages paid to the person your defective software harmed. I’m publishing them back to back on purpose, because if you only track one you’ll misjudge your exposure. A regulator fining you and a claimant suing you are two separate doors, and after this summer both are open. I have been circling the regulatory door for a while — why “we use ChatGPT” isn’t an AI strategy, what happens when the model itself becomes the attacker, whether you can still tell an open-weight model from a frontier one. August 2 is the EU answering a slice of those questions with an enforcement budget attached. What Actually Changed on August 2 Here’s the part that confuses people, so let me be precise: August 2, 2026 did not create new obligations. The substantive rules for general-purpose AI (GPAI) models kicked in a full year earlier, on August 2, 2025. What was missing until now was the enforcement machinery. For twelve months the AI Act’s GPAI chapter has been law you could technically break without anyone able to do much about it. That grace period is over. As of August 2, 2026, the AI Office, the Commission’s dedicated AI enforcement body, has four concrete powers it did not have on August 1: Demand your documentation. It can require a GPAI provider to hand over technical documentation and information about the model. Evaluate your model. It can run its own assessments of your model to check compliance and investigate systemic risk — including requesting access. Order compliance measures. It can require you to “take appropriate measures” to bring the model into line. Pull the model. In the worst case it can make you restrict its availability, withdraw it, or recall it from the EU market. One precision point worth keeping straight, because the lawyers reading this will: the AI Office is the operational body that investigates, evaluates, and builds the case, but the formal decision to fine under Article 101 is the European Commission’s. In practice you deal with the AI Office; the signature on the penalty is the Commission’s. And behind all four sits the number that focuses minds: fines of up to 3% of global annual turnover or €15 million, whichever is higher, under Article 101. Note that’s the GPAI-specific ceiling; the Act’s headline 7%-of-turnover fines are for deploying prohibited AI practices, a different regime. But for a frontier lab, 3% of global turnover is a board-level number. Figure 1. How enforcement actually lands: a non-compliance gap that survives the AI Office’s escalation ladder — documentation request → model evaluation → compliance order — ends in a fine of up to 3% of global turnover or €15M, and at the extreme, restriction or withdrawal from the EU market. So nothing about your model’s obligations changed this week. What changed is that ignoring them now has a price, a referee, and a stop button. And here is the tell that this date is real. The EU’s Digital Omnibus — a simplification package the industry lobbied for hard, tabled in November 2025 and agreed this spring — postponed the AI Act’s high-risk deadlines, sliding the Annex III obligations to December 2027 and embedded systems into 2028. It left GPAI alone. Of all the deadlines Brussels was pressed to move, the one it would not move is the one this post is about. When a regulator blinks on nearly everything except the thing you are writing about, that thing is the priority. Who This Actually Hits The AI Act is fussy about roles, and the fine print matters. The GPAI obligations land on the provider of the model — the lab that trains and places the general-purpose model on the market. Think the obvious frontier names, but also the growing field of open-weight labs, and, importantly, anyone who fine-tunes or substantially modifies a model to the point of becoming, in effect, its new provider. The Commission’s own guidance puts a rough line on that: modify a model using more than about a third of its original training compute and you’re presumed to have become a provider yourself, with the obligations that follow. That clause is the one that pulls a lot of companies who think of themselves as mere “users” into scope without noticing. If you’re a deployer — you build a product on top of someone else’s model — most of these GPAI duties are not directly yours yet (your day comes later, once the high-risk-system rules bite — a timeline the Digital Omnibus just pushed back and made conditional on technical standards). But you inherit the consequences: the transparency information your upstream provider must now give you is exactly the material your own compliance, and your own security review, depend on. Which is the first place a security practitioner should perk up: the Act is forcing your model vendor to tell you things they previously treated as trade secrets. Use that. The Baseline: What Every GPAI Provider Now Owes For every general-purpose model on the EU market, regardless of size, four duties: Technical documentation. A detailed, maintained dossier on the model — architecture, training process, intended and excluded uses, energy consumption — retained for ten years and produced to the AI Office on request. This is the file that gets read aloud in an investigation. Downstream transparency. You must publish contact details and respond to downstream providers’ requests with the information they need to integrate the model responsibly — the Code of Practice’s transparency guidance points at a short, days-long response window (law-firm readings cite roughly 14 days) — while still protecting legitimate IP and trade secrets. The “it’s all proprietary, figure it out yourself” era of model integration is ending. A copyright policy with actual mechanics. Not a paragraph of intent — a working policy that respects technological protection measures, excludes known piracy sources, honors robots.txt and machine-readable opt-out signals, and gives rightsholders a contact and a complaint path. This is the provision the training-data lawsuits will hang on. A public training-data summary. A filled-in AI Office template summarizing what the model was trained on. Not the dataset, but enough of a summary that the black box gets a label. None of this is exotic to anyone who has run a mature engineering shop. What’s new is that it’s mandatory, enforceable, and discoverable. Systemic Risk: When the Regulation Starts Speaking My Language Here is the section that made me want to write this post. A subset of models, those with “high-impact capabilities” (presumed once training compute crosses 10^25 FLOP) plus any others the Commission designates, are classified as carrying systemic risk. And the obligations that attach to them could have come straight off one of my own engagement checklists: A safety and security framework (the timing specifics here come from the Code of Practice’s safety-and-security chapter), stood up within weeks of notification and finalized before the model ships. Model evaluations and adversarial testing — the Act says red-teaming out loud. State-of-the-art evaluation of the model’s dangerous capabilities is now a legal duty, not a nice-to-have your safety team fights for budget on. Systemic-risk assessment and mitigation across the lifecycle: filtering, monitoring, input/output controls. Serious-incident reporting to the AI Office and national authorities on staggered timelines — an actual incident-response obligation for models. Cybersecurity protection of the model and its physical infrastructure — i.e., protect the weights. Weight exfiltration is now a compliance failure, not just an embarrassing headline. Ten-year documentation retention, and a safety-and-security report including external evaluators’ findings. A fair note on sourcing: the Act itself sets these duties at the level of principle (Article 55); several of the concrete specifics above — the framework’s timing, the exact shape of the safety report — come from the Code of Practice’s safety-and-security chapter, which is the paved road for demonstrating you met the statutory bar. The duty is law; some of the detail is the Code. Read that list and then reread what I wrote after the Hugging Face / OpenAI model-evaluation incident: most defenders have zero telemetry at the model and agent layer, and the tooling to run a full intrusion at machine speed is now something you can trigger by accident during your own safety testing. The AI Act just made the telemetry, the evaluation, and the incident reporting for that exact layer a regulated obligation for systemic-risk models. I don’t love every line of this Act, but I’m not going to pretend that mandating adversarial testing and weight security for the most capable models on Earth is the part worth complaining about. It’s the part I’ve been asking for. There’s also a subtle security-economics point. Adversarial testing is only as good as the adversary. A regulation that requires red-teaming without defining rigor invites the checkbox versi [truncated for AI cost control]