Verlags vs. AI News 2026: Who is liable when AI hallucinates?

Traditional media organizations are based on the principle of editorial responsibility. Every publication (in theory) passes through a control system. In cases of personality rights violations or defamation, liability under press law is clearly defined.

AI news, by contrast, is often generated by large language models (LLMs) that aggregate and recombine information from the web.

• The responsibility vacuum: Who is the “author” when AI generates false information? The model developer, the website operator, or the user who entered the prompt?
• Legal grey area: For a long time, AI systems were considered mere tools. In 2026, however, laws increasingly hold the entity placing the system on the market (i.e., the website operator) liable for the output, regardless of whether a human reviewed the text.

The EU AI Act is the central instrument regulating AI content. For media companies, it introduces three key obligations:

• Transparency obligation: Any text, image, or audio file substantially generated by AI must be clearly labeled.
• Disclosure of training data: Publishers (if training their own models) must disclose whether they used copyrighted material from other media organizations.
• Risk management: Systems that influence public opinion (news bots) are subject to enhanced oversight to prevent bias and discrimination.

Using AI in journalism is a data protection balancing act. When AI models analyze user behavior or personalize news feeds, large volumes of personal data are processed.

• Right of access: In 2026, readers have the right to know whether an algorithm decided which news they are shown.
• Data sovereignty: Transferring user data to AI servers in third countries (e.g., the US or China) is often unlawful without explicit consent and additional safeguards.

AI systems suffer from “hallucinations” - they invent facts that sound plausible. In journalism, this is fatal.

• Lack of context: AI does not understand political nuance or ethical responsibility. It optimizes for probability, not truth.
• Bias risk: If training data is biased, the AI reflects these prejudices in reporting, potentially causing severe compliance issues.

Fighting disinformation in 2026 is a technological arms race.

• Automated fact-checking: Publishers use AI tools to verify incoming information against validated databases in real time.
• Human oversight: The “human-in-the-loop” remains indispensable. Only a human can provide the final moral and legal assessment of a report.

Successful media organizations in 2026 rely on hybrid models:

• AI for structure: Automated generation of summaries, transcriptions, and standardized reports (weather, stock market).
• Humans for substance: Investigative journalism, opinion pieces, and final editorial approval (proofreading).
• Transparent labeling: A clear notice (“This text was created with the support of AI”) strengthens reader trust.

Recent developments from massive password leaks at TikTok and Instagram to the high-frequency threat landscape faced by the German Federal Bank make one thing clear: we are living in an era of constant digital exposure. In this environment, purely technical defense is no longer enough.

The year 2026 marks a turning point where transparency obligations (as required by the GDPR and the EU AI Act) and technical resilience become inseparable. Whether informing users about data flows to insecure third countries such as China or labeling AI-generated media content, trust can only be rebuilt through complete openness.

For companies and publishers, this means:

• Technology alone is not enough: Hybrid models combining AI efficiency with human expertise and editorial oversight are the only way to ensure quality and compliance.
• Responsibility cannot be delegated: Liability for data breaches or AI errors remains - legally and morally - with the operator.
• Proactive preparation: Implementing security standards such as MFA, encryption, and robust incident response management now determines market viability and survival in cyberspace.

Ultimately, stricter regulation through laws such as the AI Act or DORA presents an opportunity: it forces us to design digital processes that are more secure, transparent, and ultimately more sustainable. Those who invest in transparency today are building tomorrow’s most valuable asset - trust.

Can I sue an AI for defamation? 

No, an AI is not a legal person. In 2026, lawsuits are directed against the operator of the media outlet that published the AI-generated content.

What happens if an AI infringes copyright? 

The legal situation is clear: whoever commercially uses the output is liable for infringing third-party rights. Publishers must therefore ensure that their AI models do not copy protected texts verbatim.

Is a small disclaimer at the end of the article sufficient? 

Under the EU AI Act, labeling must be clear and easily recognizable.