Most AI regulation, for most developers, has been something that happens to other people. Risk classifications, conformity assessments, notified bodies — the kind of thing where you nod, assume legal will handle it, and go back to your streaming handler.
Article 50 is different, and it went live on 2 August 2026. It's the part of the EU AI Act that doesn't care whether your system is "high risk." It cares about one thing: can the person on the other end tell that this is AI? If the answer is no, you owe them a disclosure — and the disclosure is a product decision, a UI decision, and in one case a file-format decision. All three land on engineering.
The Commission adopted its guidelines on Article 50 on 20 July 2026, and the AI Office published a Code of Practice on Transparency of AI-Generated Content on 10 June 2026. Between those two documents and the article text itself, the shape of what you have to build is now reasonably clear. This is that shape, translated into work items.
First: does this apply to you?
Two questions, and you're probably in scope on both.
Are you a provider or a deployer? The Act splits duties. A provider develops an AI system (or has one developed) and places it on the market under its own name — if you built the chatbot or the image generator, that's you. A deployer uses an AI system under its own authority — if you dropped someone else's model into your support widget, that's you. Article 50 assigns two obligations to providers and two to deployers, and plenty of teams are both.
Does the EU reach you? The Act's territorial hooks (Article 2) are not "are you an EU company." They're closer to "is the system placed on the EU market, or is its output used in the EU." A US startup with EU users is in scope. This is the GDPR pattern, and it caught a lot of people by surprise the first time.
Not in scope: things that don't interact with people or generate content for them. The Commission's guidelines explicitly put spam filters and automated translation tools outside Article 50(1), and voice assistants and chatbots inside it.
Obligation 1 — tell people they're talking to an AI
Providers shall ensure that AI systems intended to interact directly with natural persons are designed and developed in such a way that the natural persons concerned are informed that they are interacting with an AI system, unless this is obvious from the point of view of a natural person who is reasonably well-informed, observant and circumspect. — Article 50(1)
This is the one that hits the most products, and it's the easiest to get wrong in a way that looks compliant.
The "obvious" carve-out is narrower than you want it to be. The test isn't "our users are technical." It's a reasonably well-informed, observant and circumspect person in the circumstances and context of use. A widget labelled "AI Assistant" in a developer tool is plausibly obvious. The same engine answering an inbound phone call in a warm, human-sounding voice is not — and voice is exactly where the gap is widest right now, because realtime voice agents are good enough that the "obvious" defence has quietly stopped being true.
Where the disclosure has to live. Article 50(5) settles the argument you're about to have with someone in a planning meeting: the information must be provided at the latest at the time of the first interaction or exposure, and it must be clear and distinguishable. That rules out:
- burying it in the Terms of Service
- a footnote in the privacy policy
- a tooltip behind a hover on a mobile UI
- disclosing on turn three, after the user has already asked something personal
Article 50(5) also requires conformity with applicable accessibility requirements — which in practice means your disclosure has to survive a screen reader, not just a design review.
What that looks like in a chat surface is boring, and boring is the point:
<!-- Rendered before the first assistant message, not after it. -->
<div class="ai-disclosure" role="note">
<strong>You're chatting with an AI assistant.</strong>
Answers are generated automatically.
<a href="/support/human">Talk to a person</a>
</div>
For voice, the equivalent is a spoken line in the first turn — before you collect anything, and in the language of the call. For an API you sell to other developers, the honest move is to pass the obligation downstream explicitly: document it, and give integrators a disclosure string they can render, because when they ship your model to end users under their own brand, the deployer duties become theirs and the design duty stays yours.
One more thing worth building while you're in there: a handoff path to a human. Article 50 doesn't mandate it. But the disclosure lands very differently when it's followed by an escape hatch, and support teams that ship AI assistants without one tend to discover the reason the hard way.
Obligation 2 — mark synthetic output so machines can detect it
Providers of AI systems […] generating synthetic audio, image, video or text content, shall ensure the outputs […] are marked in a machine-readable format and detectable as artificially generated or manipulated. — Article 50(2)
This is the genuinely hard engineering item, and it's the one with a different deadline (more on that below).
Two properties are required, and they're not the same thing:
- Machine-readable marking — metadata that a downstream system can parse.
- Detectability — the output can be recognised as artificially generated or manipulated.
The Act asks for solutions that are "effective, interoperable, robust and reliable as far as this is technically feasible" — a standard that explicitly bends to the state of the art. It also carves out assistive editing functions and systems that do not substantially alter the input data. Your auto-crop and your denoise filter are not in scope. Your "generate a product photo from this prompt" endpoint is.
What the Code of Practice points at. The AI Office's Code, published 10 June 2026, describes a layered approach rather than a single mechanism: signed, timestamped provenance metadata — where C2PA is the standard identified as meeting those criteria — plus an imperceptible watermark embedded in the content itself, robust enough to survive ordinary transformations like compression, cropping, scaling and format conversion. The Code is voluntary and, at the time of writing, going through an adequacy assessment by the Commission and the AI Board. Adhering to it is a route to demonstrating compliance; not adhering means you have to show equivalently adequate means of your own.
In practice, for images and video, that means attaching C2PA Content Credentials at generation time. The Content Authenticity Initiative ships open-source tooling for this — c2pa-rs with Python, JS, C++, Swift and Android bindings, plus a c2patool CLI — so this is a library integration, not a research project.
The assertion that carries "this was AI-generated" is the IPTC digital source type, referenced inside a c2pa.actions assertion:
{
"assertions": [
{
"label": "c2pa.actions",
"data": {
"actions": [
{
"action": "c2pa.created",
"digitalSourceType":
"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia"
}
]
}
}
]
}
trainedAlgorithmicMedia is the IPTC code for content created by a generative model. There are neighbouring codes for composites and for algorithmically edited media — pick the one that actually describes what your pipeline did, because "created" on a system that only retouched is its own kind of wrong. Verify the current assertion shape against the C2PA spec before you ship; the standard is still moving.
Three things nobody tells you in the compliance deck:
- Metadata gets stripped. Plenty of platforms re-encode uploads and discard provenance metadata on the way in. Signing at generation is necessary; assuming it survives the internet is not. This is precisely why the Code pairs metadata with a watermark instead of trusting either alone.
- Text is the weak link. Machine-readable marking of text has no equivalent of C2PA that works after a copy-paste. Statistical watermarking of token distributions exists, degrades under paraphrase, and doesn't survive a user retyping the paragraph. The Act's "as far as technically feasible" language is doing real work here — but "hard" is not "exempt," and documenting your reasoning is part of the deliverable.
- Sign server-side. Any marking applied in the browser is marking a determined user can skip. The signature belongs on the generation path, before the bytes reach a client.
If you're generating images or video in a product today, this obligation is now a line item in your media pipeline, not a policy question.
Obligation 3 — emotion recognition and biometric categorisation
Deployers of an emotion recognition system or a biometric categorisation system shall inform the natural persons exposed thereto of the operation of the system, and shall process the personal data in accordance with [the GDPR and related instruments]. — Article 50(3)
Shorter, and mostly a matter of knowing that it applies to you. If your product infers emotional state from voice, face or text, or sorts people into categories from biometric data, you inform the people exposed to it — and you're squarely in GDPR territory on top, usually with special-category data.
Before you scope the disclosure: check Article 5 first. Some emotion recognition — in the workplace and in education — is prohibited outright, not merely subject to transparency, and has been since February 2025. Article 50 is the wrong chapter to be reading if that's your use case.
Obligation 4 — deepfakes and public-interest text
Deployers of an AI system that generates or manipulates image, audio or video content constituting a deep fake, shall disclose that the content has been artificially generated or manipulated. — Article 50(4)
Note the split from Obligation 2: marking the file is the provider's duty; disclosing to the audience is the deployer's. If you use a third-party model to produce a synthetic spokesperson for a campaign, the vendor's C2PA manifest doesn't discharge your obligation. You still have to tell the audience.
Two carve-outs matter:
Artistic and satirical works. Where the content is part of an evidently artistic, creative, satirical or fictional work, the disclosure shrinks to revealing the existence of generated content in an appropriate manner that does not hamper the display or enjoyment of the work. A film doesn't need a permanent banner across the frame.
Text on matters of public interest. AI-generated or manipulated text published to inform the public on matters of public interest must be disclosed — unless it has undergone human review or editorial control and a natural or legal person holds editorial responsibility. This is the clause every content-heavy site should read twice. An unreviewed AI-written news summary needs a label. The same article with a named editor who checked it and owns it does not. If your publishing workflow can't currently prove which of those two happened, that's the actual gap — and it's a workflow problem before it's a legal one, which is why content operations built on AI now need an audit trail as much as a style guide.
The deadlines, which are not all the same
The Digital Omnibus on AI — published in the Official Journal on 24 July 2026 and in force since 27 July — shifted several AI Act dates. Article 50 came out of it mostly intact:
| What | Applies from |
|---|---|
| Article 50(1) AI-interaction disclosure | 2 August 2026 |
| Article 50(3) emotion recognition / biometric categorisation | 2 August 2026 |
| Article 50(4) deepfake and public-interest text disclosure | 2 August 2026 |
| Article 50(2) marking, systems placed on the market on or after 2 Aug 2026 | 2 August 2026 |
| Article 50(2) marking, systems placed on the market before 2 Aug 2026 | 2 December 2026 |
| Annex III high-risk obligations (Chapter III) | deferred to 2 December 2027 |
| High-risk AI embedded in regulated products (Annex I) | deferred to 2 August 2028 |
That last pair is the source of most of the confusion in the room right now: the high-risk regime got a long deferral, and a lot of teams heard "the AI Act got pushed back" and stopped reading. Article 50 did not get pushed back. The only grace period is the marking obligation for generative systems that were already on the market, and it expires on 2 December 2026.
Enforcement sits with national market surveillance authorities, the AI Office and — for EU institutions — the European Data Protection Supervisor. Breaching Article 50 carries fines of up to €15 million or 3% of worldwide annual turnover, whichever is higher.
A ship checklist
Pin this to the epic:
- [ ] Inventory every surface where an AI system talks to a person — chat, voice, email autoresponders, in-app agents. Each one gets a first-interaction disclosure or a written argument for why it's obvious.
- [ ] Disclosure rendered before the first AI output, accessible, in the user's language, not in the ToS.
- [ ] Every generative endpoint identified as provider-side or deployer-side. Write it down; vendor contracts should say the same thing.
- [ ] C2PA Content Credentials signed server-side on image/audio/video generation, with the correct IPTC
digitalSourceType. - [ ] Watermarking assessed for each modality; where it isn't feasible, the reasoning is documented rather than assumed.
- [ ] Deepfake disclosure at the publication surface, not just in the file metadata.
- [ ] Editorial-review provenance recorded for AI-assisted public-interest text — who reviewed, when, who owns it.
- [ ] Emotion recognition / biometric categorisation checked against Article 5 prohibitions before anything else.
- [ ] Disclosure copy and placement covered by a test, so the next redesign doesn't silently delete it.
Conclusion
The thing that makes Article 50 unusual, as regulation goes, is how little of it is paperwork. There's no conformity assessment here, no technical documentation dossier, no notified body. There's a banner that has to render before the first message, a signature that has to happen on the generation path, a label that has to reach the audience, and a record of who reviewed what. Four engineering tickets, roughly, and none of them are hard.
They're just easy to defer — and the deferral is what gets expensive. Article 50 is now enforceable, the guidelines are published, the Code of Practice exists, and the tooling for the hard part is open source. Compliance here is mostly a question of whether someone put it in the sprint.
The teams that will have the least trouble with this aren't the ones with the biggest legal department. They're the ones that were already willing to tell users, plainly, what the machine was doing. Turns out that was always the good product decision — it just became the required one.
Written by the team behind Cursuri-AI.ro, an AI education platform with hands-on English-language courses on AI, data privacy and EU AI Act compliance, production LLM integration, and shipping AI products.
Sources & further reading:
- EU AI Act — Article 50: Transparency Obligations for Providers and Deployers of Certain AI Systems (full text, exemptions, codes of practice)
- European Commission — Guidelines on transparency obligations for providers and deployers of certain AI systems (adopted 20 July 2026)
- European Commission — Code of Practice on Transparency of AI-generated Content (published 10 June 2026)
- Content Authenticity Initiative — open-source C2PA SDKs and
c2patool - IPTC — Digital Source Type NewsCodes vocabulary (
trainedAlgorithmicMediaand related values)
This article is educational content written by engineers, not legal advice. Article 50 interacts with the GDPR, the DSA, national implementing rules and sector regulation, and the Digital Omnibus changed several dates in 2026 — verify against current official sources and your own counsel before shipping.
Top comments (0)