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Short answer: The EU AI Act regulates an AI system according to its intended purpose and the context in which it is used. It separates prohibited practices, which cannot lawfully be placed on the EU market or used except where a narrowly written exception applies; high-risk systems, which must meet extensive safety, governance and documentation requirements; and systems subject mainly to transparency duties, including chatbots, synthetic media and some biometric or emotion-recognition tools.
The first prohibitions and AI-literacy duties have applied since 2 February 2025. Article 50 transparency obligations apply from 2 August 2026, with a limited transition for certain systems already on the market. A later prohibition covering non-consensual intimate material and child sexual abuse material applies from 2 December 2026. High-risk rules arrive in further stages through 2027 and 2028.
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How the EU AI Act classifies an AI system
Classification is not based simply on whether a product uses machine learning, generative AI or an algorithm. The decisive questions are what the system is designed to do, who uses it, who may be affected and the surrounding deployment context. The same underlying model can therefore fall into different obligations when integrated into different products or workflows.
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| Category | What it means | Main consequence |
|---|---|---|
| Prohibited AI practices | Uses the Act bans because of unacceptable risks to safety, rights or autonomy. | The practice must not be placed on the EU market, put into service or used, subject to any tightly defined exception. |
| High-risk AI | Systems listed in high-risk rules or used as safety components of regulated products. | Providers and deployers face risk-management, data, documentation, oversight, accuracy, cybersecurity, registration and incident obligations. |
| Transparency-only systems | Systems that interact with people, generate or manipulate content, or perform specified emotion-recognition or biometric-categorisation functions. | People must receive notices, and qualifying synthetic content must be labelled or machine-readable as AI-generated or manipulated. |
A system can have more than one relevant duty. For example, a generative system may need to apply Article 50 content-marking rules while a separate deployment of the same technology could also be high-risk because of its purpose.
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Which AI uses are prohibited?
The Commission’s “Navigating the AI Act” material gives examples, but the regulation’s legal text and Commission guidance determine the exact scope. Treat the examples below as practical indicators, not a substitute for analysing the wording of the applicable provision.
Manipulative or exploitative systems
AI designed to materially distort a person’s behaviour through manipulative or deceptive techniques can be prohibited where the conditions in the Act are met. The analysis focuses on the system’s design, the vulnerability or circumstances of affected people and the resulting or likely harm. A normal recommendation feature is not automatically prohibited; its purpose and operation matter.
Social scoring
Systems that evaluate or classify people over time using social behaviour or known, inferred or predicted personal characteristics can be prohibited when they produce the types of detrimental or unjustified treatment addressed by the Act. A private organisation cannot avoid the rule merely by calling a score a “trust,” “reputation” or “risk” indicator.
Specified biometric practices
The Act restricts several biometric uses. Whether a particular camera, identification or categorisation system is prohibited depends on the biometric function, the people affected, the purpose and the applicable exception. Do not assume that every facial-analysis or biometric tool is in the same legal category: some are prohibited, some are high-risk and some trigger transparency duties.
Real-time remote biometric identification by law enforcement
Real-time remote biometric identification in publicly accessible spaces for law-enforcement purposes is listed as a prohibited example, but the Act provides narrow exceptions. An organisation considering such a deployment must identify the precise legal basis and conditions for the exception rather than treating public-safety goals as a general permission.
Nudification, non-consensual intimate material and CSAM
The Commission lists “nudification” applications and systems that generate non-consensual sexually explicit or intimate content or child sexual abuse material (CSAM). The Commission’s framework states that the later prohibition was introduced as part of the AI Omnibus and comes into effect in December 2026. The enforcement timetable specifies 2 December 2026 for the prohibition relating to generation or manipulation of non-consensual intimate material and CSAM. Existing products should be reviewed before that date; launching a new feature shortly beforehand does not remove the need to meet the rule when it applies.
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When did the first prohibitions apply?
Prohibitions 1 through 8 entered into application on 2 February 2025, along with the Act’s AI-literacy obligations. The ninth prohibition described above applies from 2 December 2026. The numbering and any exception must be checked against the current legal text and Commission guidance because amendments and implementing measures can affect practical interpretation.
When is an AI system high-risk?
High-risk status generally arises in two ways: the system is used for a high-risk purpose listed by the Act, or it is an AI safety component of a product governed by specified EU product-safety legislation. The Commission’s guidance identifies sensitive areas including biometrics, critical infrastructure, education, employment, migration, asylum and border control.
Common high-risk purposes
- Assessing access to or selection for a job.
- Evaluating access to education or training.
- Assessing eligibility for credit or other essential services.
- Supporting decisions about medical treatment or access to healthcare.
- Certain policing and law-enforcement risk assessments.
- Safety components in regulated products, such as some robots, drones or medical devices.
The intended purpose must be documented precisely. “General analytics” is too vague to support a reliable classification. Describe the decision being supported, the people affected, the environment in which the system operates and whether an output can influence a person’s rights or access to an essential opportunity.
Provider obligations
Before placing a high-risk system on the market or putting it into service, the provider must complete the applicable conformity-assessment route. Continuing duties cover the whole lifecycle, not just the launch review.
- Risk management: identify, estimate and reduce foreseeable risks, then keep the process under review as the system and its environment change.
- Data governance and quality: use relevant, sufficiently representative and appropriately governed data for development and operation, with controls for errors and bias relevant to the intended purpose.
- Documentation and traceability: maintain technical documentation, records and logs that allow the system and significant events to be understood and audited.
- Human oversight: design effective supervision, including the ability to interpret outputs, detect anomalies and intervene or stop use when necessary.
- Accuracy, robustness and cybersecurity: specify performance expectations, resist foreseeable errors and attacks, and keep the system dependable under the conditions for which it is intended.
- Quality management: operate documented processes for design, testing, monitoring, corrective action and post-market controls.
- Registration: register the system where the Act requires it.
- Incident response: report serious incidents and take corrective action, including withdrawal or modification where required.
Deployer obligations
A deployer is the organisation or person using an AI system under its authority, rather than the entity that developed or supplied it. Deployers must follow the provider’s instructions, monitor operation and identified risks, appoint a person responsible for human oversight and ensure that input data is relevant and sufficiently representative for the task.
Public authorities and organisations providing public services must carry out a fundamental-rights impact assessment before the first use of a relevant high-risk system. Workplace deployments, public-service uses and systems supporting decisions about people can also trigger additional notice and registration duties. Keep evidence of the assessment, oversight assignment, monitoring results and corrective actions; a policy that exists only on paper is difficult to defend after an incident.
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High-risk implementation dates
The Commission’s planning dates distinguish two groups. High-risk use cases listed in Annex III are scheduled to apply from 2 December 2027. High-risk AI embedded in regulated products is scheduled for 2 August 2028. Organisations should use these dates for project planning, but check transitional provisions and sector-specific measures before relying on them as a launch deadline.
What Article 50 requires for chatbots, generative AI and deepfakes
Article 50 transparency duties apply from 2 August 2026. They address four recurring situations: a person interacts directly with an AI system; a person encounters synthetic content whose artificial origin can reliably be verified; a system performs emotion recognition or biometric categorisation; and a person encounters a deepfake or specified public-interest text published without human review or editorial control.
Disclose direct AI interaction
Providers of systems that directly interact with people must inform them that they are interacting with AI unless that fact is obvious from the circumstances. The notice should appear at the point of interaction, not only in a distant privacy policy or terms page. A conversational service should make the disclosure visible before or at the beginning of the exchange and preserve it when the interface changes.
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Providers of generative systems must ensure qualifying synthetic audio, image, video or text is marked in a machine-readable format and can be detected as artificially generated or manipulated. The requirement is technical as well as visual: a caption alone may not satisfy a machine-readability obligation. Build the marking into the generation or export pipeline and test that downstream systems can detect it.
Notify people about emotion recognition and biometric categorisation
Deployers must inform people when they use an emotion-recognition or biometric-categorisation system. The notice should identify the operation before or when the person is exposed to it, so affected people are not left to infer the practice from a later document.
Label deepfakes and certain public-interest text
Deployers must clearly label deepfakes. They must also label AI-generated or manipulated text published on matters of public interest when there has been no human review or editorial control. Human review and editorial control are therefore important factual conditions, not decorative wording: document who reviewed the material, what was checked and when the decision was made.
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Transition for systems and existing content
| Situation | Rule or date |
|---|---|
| Article 50 generally | Applies from 2 August 2026. |
| System placed on the market before 2 August 2026 | Receives until 2 December 2026 for the Article 50(2) marking and detection obligation. |
| Content generated before 2 August 2026 | Does not need retroactive labelling under the stated transition explanation. |
Providers established or located outside the EU are covered when the output of their AI system is used in the EU. Location of the vendor alone is therefore not a reliable way to decide whether Article 50 controls apply.
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Start by mapping the supply chain. A provider develops an AI system or has one developed and places it on the market or puts it into service under its name or trademark. A deployer uses the system in an organisation or activity. Importers, distributors, product manufacturers and authorised representatives can have additional duties depending on their role and the system’s route to market.
For each system, record the legal entity responsible for development, the entity procuring or configuring it, the operating location, the affected population, the intended purpose and any integration into a regulated product. This role map prevents a common failure: assuming that a vendor’s contract or conformity statement transfers every duty away from the organisation that actually deploys the system.
Penalties and enforcement
National competent market-surveillance authorities are the main enforcers. The AI Office has a more limited role for specified general-purpose-AI situations and certain very large online platforms or search engines. The European Data Protection Supervisor enforces the Act for EU institutions, bodies and agencies.
| Type of infringement | Maximum stated fine | Qualification |
|---|---|---|
| Prohibited AI practices | Up to €35 million or 7% of the offender’s total worldwide annual turnover, whichever is higher. | This is the highest penalty tier identified by the Commission’s enforcement framework. |
| Article 50 transparency duties | Up to €15 million or 3% of total worldwide turnover for the preceding financial year. | Fines are subject to proportionality, including consideration for SMEs and small mid-cap companies. |
These are maximum figures, not automatic tariffs. The competent authority, the facts, the organisation’s size and proportionality all matter. Nevertheless, the percentage calculation means a multinational’s exposure can greatly exceed the fixed euro amount.
A practical compliance workflow
- Inventory every AI use. Include internally built tools, vendor features, APIs, embedded functions and pilots. Record the version, owner, users, data and business process.
- Write the intended purpose. State what the system actually influences, who may be affected and whether a human can override the result. Avoid broad labels such as “automation” or “insights.”
- Screen for prohibited practices first. Check manipulation, exploitation, social scoring, biometric uses, law-enforcement identification and the non-consensual intimate-material or CSAM prohibition with the correct effective date.
- Assess high-risk status. Compare the purpose and product integration with the relevant high-risk categories, then identify whether the 2027 or 2028 implementation timetable applies.
- Assign roles and evidence owners. Name the provider, deployer, importer or other responsible parties. Allocate ownership for technical documentation, data governance, human oversight, registration and incident reporting.
- Implement Article 50 controls. Add interaction notices, machine-readable content marking, biometric or emotion-recognition notices and deepfake or public-interest text labels where applicable. Test them in the actual user interface and export formats.
- Test and monitor in operation. Measure accuracy and robustness for the intended conditions, monitor drift and incidents, review input-data representativeness and record interventions or shutdowns.
- Check national supervision. Identify the competent market-surveillance authority for the sector and country, and confirm any registration, reporting or public-sector impact-assessment process before deployment.
Common mistakes that create avoidable risk
Classifying the model instead of the use
A foundation model or software package does not have one universal Act classification. Reassess when the purpose, users, data, autonomy or environment changes.
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Confusing transparency with permission
Labelling a deepfake or notifying a person about a chatbot does not legalise a prohibited practice or satisfy high-risk controls. Transparency is an additional duty, not a safe harbour.
Relying on a human in name only
Assigning an employee to “review” outputs is not effective oversight if that person lacks authority, time, training or access to the information needed to challenge the system. Define escalation, intervention and stop-use procedures.
Ignoring machine-readable marking
A visible “AI-generated” note can be useful to people but may not meet the technical marking requirement. Preserve the required signal through editing, storage, publication and syndication workflows.
Using a vendor’s date as the compliance date
Article 50 can apply when output is used in the EU even if the provider is outside the EU. Conversely, transition rules depend on when the system was placed on the market and when content was generated, not simply on when a contract was signed.
EU AI Act timetable at a glance
| Date | Milestone |
|---|---|
| 2 February 2025 | Prohibitions 1–8 and AI-literacy obligations apply. |
| 2 August 2026 | Article 50 transparency duties apply. |
| 2 December 2026 | The prohibition covering generation or manipulation of non-consensual intimate material and CSAM applies; systems placed on the market before 2 August 2026 receive the stated deadline for Article 50(2) marking and detection. |
| 2 December 2027 | Annex III high-risk use-case rules are scheduled to apply. |
| 2 August 2028 | High-risk AI embedded in regulated products is scheduled to apply. |
The regulation, Commission guidance, implementing measures and amendments control the legal result. Before relying on a classification, verify the current sector rules, the system’s intended purpose, your role in the supply chain, the applicable transition provision and the competent national supervisory authority. This article is an operational explanation, not legal advice.
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