The European Commission has published a voluntary Code of Practice on Transparency of AI-Generated Content, giving AI providers and deployers a concrete path to compliance with the AI Act’s labeling requirements—and a clear reason to sign up.

The code, released June 10, 2026, covers two broad categories of obligations. Section 1 targets providers of generative AI systems, requiring them to mark outputs—audio, image, video, and text—in machine-readable formats and ensure their detection as artificially generated or manipulated. The technical solutions must be effective, interoperable, and reliable “as far as technically feasible,” factoring in content type, implementation costs, and the state of the art. Section 2 targets deployers, requiring them to label deepfakes (audio, image, or video that falsely appears authentic) and disclose AI-generated or manipulated text publications on matters of public interest.

The Commission also released a set of standard icons that deployers can use to label AI-generated content. Nicholas Diakopoulos, a professor at Northwestern University, shared them on LinkedIn:

The code is currently under adequacy assessment by the Commission and the AI Board. Once it clears that review, signatories can rely on its measures to demonstrate compliance with Article 50 of the AI Act, reducing administrative burden and gaining legal predictability across all EU member states. Non-signatories will have to demonstrate adequate compliance individually, assessed case-by-case by national market surveillance authorities.

Signatories also gain access to Signatory Taskforces: working groups set up to share implementation practices and advance marking and detection techniques across the value chain.

The code is described as a “consistent, practical and proportionate” implementation framework, not a replacement for the AI Act or the Commission’s forthcoming guidelines on Article 50’s scope.

The code was developed over three drafting rounds between September 2025 and June 2026, led by an independent chair and vice-chair. Participants included AI system providers, detection developers, industry associations, civil society organizations, academic experts, and organizations with expertise in transparency and very large online platforms. International and European observers also contributed without voting rights. Two dedicated working groups handled the providers and deployers tracks separately.

Key milestones included a first drafting round starting November 5, 2025, a second round in January 2026, a third round in March 2026, and a closing plenary on June 10, 2026—the same day the code was published.

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Fake AI-generated videos of Venezuelans celebrating President Nicolás Maduro’s capture flooded social media this week. The clips looked real enough. But the more troubling part wasn’t how convincing they were.

It was who was sharing them.

As John Herrman writes in New York Magazine’s Intelligencer, Elon Musk widely shared and reposted the fabricated celebration videos to his massive following. That’s notable because Musk is “perhaps the best equipped in the entire world to know that they weren’t real.” He runs an AI company connected to a social network with a fact-checking system.

The old hypothesis about AI disinformation assumed bad actors would trick unsuspecting masses with realistic fake videos. The reality is stranger.

“They were passed around by a powerful person with a large following…for an audience of people who do not care whether they are” real, Herrman writes.

Even X’s own chatbot Grok got duped. Reuters reports the bot initially told users the video “shows real footage of celebrations in Venezuela.” It later acknowledged the video “appears to be manipulated” only after being challenged.

The clips served as what Herrman calls “ambient ideological slop for backfilling a desired political reality.” They weren’t meant to persuade skeptics. They gave true believers something satisfying to share.

This creates a new challenge for newsrooms. Traditional fact-checking assumes people want the truth but lack access to it. What happens when the audience treats reality as optional?

The answer may be sobering. AI disinformation isn’t primarily causing chaos or confusion. Instead, Herrman writes, it’s creating “a perverse form of order in which persuasion is unimportant, disinformation is primarily directed at ideological allies, and everyone gets to see exactly what they want.”

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Within hours of Nicolás Maduro’s arrest by U.S. forces, fake AI-generated images of Venezuela’s ousted president spread across social media faster than newsrooms could verify them.

The incident marks one of the first times synthetic imagery has depicted a major figure during a rapidly unfolding news event, according to a New York Times report by Stuart A. Thompson and Tiffany Hsu.

“This was the first time I’d personally seen so many A.I.-generated images of what was supposed to be a real moment in time,” Roberta Braga, executive director of the Digital Democracy Institute of the Americas, told the Times.

Some fake images made it into Latin American news outlets before being quietly replaced with an official photo shared by President Trump. NewsGuard, which monitors the reliability of online information, tracked five fabricated images and two misrepresented videos that collectively drew more than 14.1 million views on X in under two days.

The Times tested a dozen AI generators and found most tools, including Google’s Gemini, OpenAI’s ChatGPT, and X’s Grok, quickly created fake arrest images despite stated policies against misleading content.

Jeanfreddy Gutiérrez, who runs a fact-checking operation covering Venezuela, said the fakes spread through “almost every Facebook and WhatsApp contact” he has before official images were available.

“It just took a lot of work, because we always lose the battle to convince people of the truth,” Gutiérrez told the Times.

A pattern of failures

That battle is getting harder. The Maduro deepfakes emerged just days after Grok became the center of a global regulatory firestorm. Governments in the EU, UK, France, India, Malaysia, and Australia have all launched investigations after the chatbot began generating non-consensual sexualized images of women and minors at scale.

Bloomberg reported that Grok was generating thousands of “undressed” images per hour earlier this week. The official Grok account posted an apology on X, writing that it “deeply regret[s]” generating sexualized images of girls “estimated ages 12-16.”

If a major image generator can’t prevent the creation of child sexual abuse material, its safeguards against political deepfakes are likely just as porous.

Gutiérrez said many people refused to believe the official image of Maduro posted by Trump was real.

“It’s funny, but very common,” he told the Times. “Doubt the truth and believe the lie.”

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UK regulators are scrambling to contain a deepfake disaster unfolding on Elon Musk’s X platform. Ofcom, the UK’s independent regulator for communications services, made “urgent contact” with xAI this week after reports that Grok, the platform’s AI chatbot, has been generating explicit images of women and children without consent.

The tool reportedly put images of Princess Catherine, celebrities and ordinary women into sexualized contexts. Users discovered they could digitally undress anyone by simply tagging Grok in a post.

Journalist Samantha Smith told the BBC she felt “dehumanised and reduced into a sexual stereotype” after discovering Grok users had targeted her photos. When she posted about the experience, others asked Grok to generate more.

Technology Secretary Liz Kendall called the situation “absolutely appalling” and called on xAI to to “urgently deal” with its chatbot. She has also backed Ofcom to take enforcement action. The European Commission labeled the outputs “illegal” and “disgusting.”

xAI’s response to journalists has been an auto-reply. Many media organizations seeking comment from the company reported receiving auto replies that said only, “Legacy Media Lies.” But under pressure from regulators in the UK, EU, India, France and Malaysia, the company has issued reactive statements. X’s Safety account said it removes illegal content and works with law enforcement. Musk posted that users who prompt illegal content will face consequences. The Washington Post reported he also responded to one complaint with a laughing emoji.

Call it “breaking verification” instead of breaking news.

This crisis illustrates why the Reuters Institute’s 2026 predictions matter for newsrooms. Harvard Shorenstein Fellow Shuwei Fang told the Institute that news organizations will discover their next product isn’t content but process: answering “Is this real?” at speed.

When fake images spread instantly and AI tools generate convincing forgeries on command, audiences need trusted sources who can quickly establish what’s authentic. News organizations with verification expertise have a product the market desperately needs.

Law professor Clare McGlynn of Durham University told the BBC that X “could prevent these forms of abuse if they wanted to” but “appear to enjoy impunity.”

In a landscape where platform owners dismiss press inquiries as lies, journalism’s verification function becomes essential infrastructure.

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