EU AI Act Article 50: What AI Agents Must Disclose

On 20 July 2026 the European Commission adopted its final guidelines on the transparency obligations in Article 50 of the EU AI Act. Those obligations start applying on 2 August 2026, thirteen days later. An agent that talks to people, generates content, or publishes text can trigger at least one of five Article 50 disclosure duties, and the guidelines are the first detailed account of what satisfying them looks like.

The practical questions are which trigger applies to which kind of agent, where the exceptions are thinner than they look, and which parts of the work the application has to do rather than the platform underneath it. For the wider risk-tier picture and the high-risk timeline, read our guide to EU AI Act compliance for AI agents .

What the Commission Published on 20 July

The package explains how the Commission reads Article 50 without changing a word of it. Alongside the guidelines the Commission issued a Communication approving their content, a public FAQ on the Article 50 obligations, and a short fact sheet. The goal is to get the same rules read the same way in every member state, so that people can tell when they are dealing with an AI system and when content was generated or altered by one.

None of it is binding. Only the Court of Justice can authoritatively interpret the Regulation. But the guidelines are the reference point that national market surveillance authorities and the AI Office will work from, so they are the best available preview of how those authorities will read the text from August onward.

The final text also confirms that the Commission assessed the Code of Practice on Transparency of AI-Generated Content as adequate. The Code was published by the AI Office on 10 June 2026 and adherence is voluntary. Signing it is a way to demonstrate compliance with the marking duties, not a formal legal presumption of compliance. Not signing it is not automatically wrong, but the provider carries the full burden of showing that the chosen marking is good enough.

Further reading: AI Omnibus (European Commission), guidelines on the transparency obligations in Article 50, guide to EU AI Act compliance for AI agents.

The Five Disclosure Triggers

Article 50 carries five separate obligations, split between the provider role and the deployer role, and a single system can trigger several of them at once.

Article 50(5) governs how all of it is delivered: clearly and distinguishably, at the latest at the first interaction or exposure, and in a form that meets accessibility requirements. For deepfakes the guidelines are explicit that a machine-readable mark alone is not enough. A person has to be able to perceive the disclosure.

The Trigger That Catches Most Agent Teams

The guidelines set four cumulative criteria for whether a system interacts directly with a natural person. All four have to hold:

• 1.The system qualifies as an AI system under the Regulation
• 2.There is a genuine two-way exchange, not merely collection of data from the person
• 3.The AI communicates with the person itself, rather than through a human intermediary
• 4.The counterpart is a natural person

That draws a usable line through a typical agent fleet. An agent answering customers over the Telegram connector, replying from a shared inbox through the email connector, or streaming into a support widget over a WebSocket session is squarely in scope. An agent that consumes a Kafka topic, enriches records, and writes to Postgres is not: there is no natural person on the other end of the exchange. Background systems and machine-to-machine communication are excluded.

The duty attaches to the provider, meaning whoever develops the system and places it on the market or puts it into service under their own name. An organization that builds an agent and offers it to customers is the provider. Because the obligation attaches at design time, the disclosure has to be built into the system rather than remembered at runtime.

The Exceptions Are Narrower Than They Look

Obviousness has a legal test behind it

Article 50(1) does not apply where it is obvious to the person that they are dealing with an AI. The guidelines measure that against a hypothetical average person who is reasonably well-informed, observant and circumspect, and they interpret the carve-out restrictively given how central transparency is to the Regulation. Being confident internally that everyone knows the support widget is a bot is a different thing from testing it against that standard and writing down the result. An authority will ask for the written version.

Editorial control means someone actually read it

The public-interest text obligation falls away where the content underwent human review or editorial control. The guidelines define that as a deliberate examination of the substance by one or more natural persons with relevant knowledge, plus a person or organisation who can approve, alter or reject the content on substantive grounds and who holds editorial responsibility for publication. Running a spellchecker over the output does not qualify, and neither does a cursory glance.

For teams shipping content agents this is the exception most likely to matter, and the one that turns into an evidence problem. Relying on it means being able to show who reviewed which output, when, and with what authority to reject it.

Marking has real carve-outs, and they are technical

Article 50(2) does not reach systems performing an assistive function that does not substantially alter the input data. The guidelines add further exclusions for short sequences of symbols, source code, machine-to-machine outputs, and closed-loop development environments. Evidently artistic, satirical or fictional works keep a reduced deepfake obligation: the disclosure must exist, but in a manner that does not hamper the display or enjoyment of the work.

The Dates That Matter

Retroactivity splits by modality, and the split is easy to get backwards. Images, audio and video generated or manipulated before 2 August 2026 do not have to be marked retroactively. Text works the other way. Text generated before 2 August but published on or after that date does need labelling, unless the editorial control exception applies. Scheduled content queues and evergreen libraries are worth checking on that basis.

Who Marks the Output With Bring Your Own Key

Article 50(2) sits with the provider of the generative system, and the technical expectations behind it live where content is produced: cryptographically signed provenance metadata, imperceptible watermarks that survive format conversion, and fingerprint registries as a supplement. The Code of Practice is explicit that no single technique currently satisfies all four quality criteria it sets out, which are effectiveness, interoperability, robustness and reliability, so it pushes providers toward layered approaches rather than one mechanism.

This affects the allocation of obligations on Connic. With BYOK, provider-side marking is a property of the selected model service. With a connic/* model, Connic supplies the managed inference path and documents the provider-side controls it relies on. In both cases, the application in front of users has separate transparency duties. Provider evidence can support the compliance record; it does not transfer responsibility.

Turning Article 50 Into an Operational Record

Disclosure duties fail audits in a predictable way. The banner exists, the label is there, and nobody can produce a dated record showing which system carries which duty, on what basis, and that the disclosure reached the person it was meant for. Connic AI Governance, an Enterprise entitlement, is where that record lives. It is documentation and evidence rather than enforcement, and it is scoped per project. The AI Governance reference covers the full workflow.

Approvals are the editorial-control paper trail

For reliance on the human review exception for public-interest text, the guidelines require substantive examination by a person who can reject the content. That is exactly what an approval gate in front of publication produces: the output, the named reviewer, the decision, and the timestamp. Together with the trace behind each run this provides evidence that the exception applies instead of merely asserting it.

Where to Start Before 2 August

• 1.List every agent whose output reaches a natural person, and note the surface it reaches them through. That list defines the Article 50(1) scope
• 2.For each one, determine the organisation's role. Building and offering the agent generally makes the organisation a provider; using another party's system under its own authority makes it a deployer, and both can apply at once
• 3.Write the disclosure copy in every supported locale, and place it so it lands at or before the first exchange rather than in a settings page or a footer
• 4.For AI-generated text on public-interest topics, choose deliberately between labelling it and running genuine editorial review, then build the evidence trail for the selected approach
• 5.Ask the model provider what marking it applies to generated media and how it can be detected, and record their answer as upstream evidence

For how Connic's controls line up against the wider Regulation, read the EU AI Act platform statement. None of this is legal advice, and a preliminary assessment is not a classification: the final call on which duties apply belongs to the organisation and its counsel.