EU AI Act enforcement is no longer theoretical. The first enforcement actions and penalties began in September 2026, and the general-purpose AI rules have been enforceable since August 2, 2026. If your products touch European users — chatbots, generated content, synthetic media, any AI interaction — the compliance clock is running. Note: this is general information, not legal advice; consult counsel for your situation.
The highest-leverage thing you can do right now is build an AI touchpoint inventory: a complete map of every place a user interacts with or receives AI-generated output across your products. Everything else — disclosures, marking, documentation — hangs off that inventory. Without it, you cannot prove coverage, and coverage is what enforcement will test.
What's enforceable right now¶
The general-purpose AI rules have been enforceable since August 2, 2026. In plain terms, that means model providers face obligations on documentation, transparency, and risk management that flow downstream to deployers — and the AI Office now has the authority to demand documents and act. September 2026 brought the first enforcement actions and penalties, which means enforcement is no longer a future threat to plan around; it is an active process to be ready for.
Article 50's disclosure duties¶
Article 50's transparency guidance is the part most product teams will feel first. It requires disclosure of AI interactions — users must be told when they are interacting with an AI system — and machine-readable marking of synthetic outputs. That covers the obvious cases (chatbots, generated articles) and the easy-to-miss ones (auto-drafted emails, AI-touched support replies, synthetic product descriptions). If a user could mistake AI output for a human's, it needs disclosure.
Build the touchpoint inventory¶
The inventory is a concrete method, not a metaphor. Enumerate every place across your products where a user interacts with an AI system or receives AI-generated output: chat interfaces, support automation, generated recommendations, synthetic media, AI-drafted notifications. For each touchpoint, record what kind of AI produces the output, what disclosure the user currently sees, and whether the output is marked. Most teams discover touchpoints they had forgotten — shadow deployments, experiments that never got turned off, vendor tools that quietly added AI features.
Synthetic-output marking in practice¶
"Machine-readable marking" means more than a disclaimer line. Operationally, it means synthetic outputs carry metadata or watermarks that machines — not just humans — can detect: metadata in media files, structured provenance signals, consistent disclosure strings. Start by batch-auditing existing assets: run your inventory against your live outputs and flag everything synthetic that is currently unmarked. The backlog is usually larger than expected, which is exactly why the inventory comes first.
Penalties and the compliance checklist¶
The stakes are stated plainly: the AI Office can demand documents and fine model providers up to 3% of worldwide turnover or €15m. The practical compliance sequence runs: inventory → disclosure points → marking → documentation → review cadence. Build the touchpoint inventory, add disclosure at each AI interaction point, apply machine-readable marking to synthetic outputs, document the whole map, and set a cadence to re-run it — because your product surface changes faster than your compliance documents.
The takeaway¶
Build the AI touchpoint inventory now, not in 2027. Enforcement is live, penalties have started landing, and the inventory is the foundation every other Article 50 obligation stands on. LawWarden's compliance templates give you a starting structure — and remember, this is general information, not legal advice: bring counsel in early.