EU tightens grip on AI: Requirements for labelling deepfakes and chatbots
On Sunday 2 August 2026, the EU began enforcement of the requirements under the AI Act. Chatbots must now be declared, and all deepfakes must be labelled with machine-readable data.
What happened?
On Sunday 2 August 2026, the first binding transparency rules of the EU AI Act came into effect. Services using AI chatbots must now clearly inform users that they are interacting with a machine. Furthermore, synthetically generated content such as deepfakes must be provided with machine-readable labelling so that it can be easily identified.
Key facts
| Startdatum för tillsyn | 2 augusti 2026 |
|---|---|
| Maximal sanktionsavgift | 3 % av global årsomsättning |
| Tillsynsmyndighet | EU AI Office & nationella myndigheter |
”AI Office is the world’s first”
Why it matters
The aim is to increase transparency and combat disinformation, fraud and copyright infringement as generative AI spreads through society. Companies that fail to comply with the rules risk having their AI models banned from the EU market and face fines of up to 3 per cent of their global annual turnover.
Who is affected?
The rules affect all companies and developers that provide AI systems or AI-generated material to users within the EU. Consumers and users will benefit from strengthened protection and clearer information regarding when they are interacting with an AI or consuming AI-created content.
Impact on the EU
The rules are applied directly and equally in all EU countries via the EU AI Act. The Commission’s new AI Office has the authority to remove non-compliant models from the entire internal market and can impose sanctions of up to 3 per cent of companies' global annual turnover.
What else you should know
According to Brando Benifei, one of the European Parliament's lead rapporteurs for the Act, the new AI Office will be the world's first regulatory body with such extensive powers over AI developers. In addition to market bans and fines, there are also requirements for transparency regarding copyrighted training data.
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