Article 50 of the EU AI Act has been in force since 2 August 2026. A lot of the coverage since then has flattened it into a single headline — “AI content must be labelled in the EU” — which is close enough to be misleading. The obligation is narrower and more specific than that, it falls on different parties depending on what they built or how they used it, and knowing which bucket you're in matters more than the headline does.
Two separate obligations, two separate parties
Article 50 doesn't create one blanket labelling rule. It creates a small set of obligations that land on different actors in the AI supply chain:
- Providers of generative AI systems have to mark the synthetic image, audio, video, or text output their systems produce as machine-readable — something a downstream system can detect, not necessarily something a human viewer notices at a glance.
- Deployers of AI systems that generate or manipulate content amounting to a deepfake have to disclose that the content is artificially generated or manipulated.
- Anyone publishing AI-generated text on a matter of public interest has to label it as AI-generated, unless it's gone through meaningful human editorial review.
Notice what that split means in practice: a tool provider's obligation is a machine-readable mark baked into the output. A deployer's obligation is a disclosure to the person seeing the content. Those are different jobs, and a compliance approach built for one doesn't automatically satisfy the other.
Not the only clock that's started running
The EU isn't the first jurisdiction to put a content-labelling regime into force, and it won't be the last. China's Measures for Labeling AI-Generated Content have required both a visible label and an embedded metadata label on AI-generated text, images, audio, and video since 1 September 2025. South Korea's AI Basic Act, in force since 22 January 2026, requires a visible label on realistic AI-generated content and an invisible watermark on stylised generated content, with penalties deferred during a grace period except in cases of serious harm.
Three different legal systems, three different mechanisms, and none of them identical to each other — visible labels, embedded metadata, invisible watermarks, machine-readable marks, in varying combinations depending on who you ask. If your content moves across borders, “we labelled it” is not a single checkbox.
Why a single AI score doesn't answer this
It's tempting to reach for one number — run the file through a detector, get back “94% AI-generated,” call the disclosure question settled. That doesn't actually map to what any of these laws ask for. Article 50's obligations turn on specific, checkable facts: was a machine-readable mark actually present in the output, was the deployer the one who generated the deepfake, was the published text meaningfully edited by a person. A single confidence percentage collapses all of that into a guess and throws away exactly the detail a disclosure decision needs.
That's the reasoning behind treating this as an evidence problem instead of a scoring problem: separate signals such as Content Credentials, embedded metadata, and watermark claims, each labelled by how certain it is, so a person can see what was actually found before they decide what to disclose. None of that is a finding that content “complies with” Article 50 or any other regime — it's evidence relevant to the disclosure call a person still has to make.
This is a general summary for orientation, not legal advice. Confirm current requirements for your jurisdiction with counsel before relying on it.