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The Regulation, in its own words

Scope, role, tier, date, in that order, because that is the order the answers depend on each other in. Nothing on this page classifies your system: it explains the categories the Act uses, and cites the provision behind every sentence.

What the Act is talking about

What counts as an AI system

Article 3(1) defines it, and the definition is broader than "machine learning" and narrower than "software". A system is in scope when it is machine-based, designed to operate with varying levels of autonomy, may exhibit adaptiveness after deployment, and infers from the input it receives how to generate outputs such as predictions, content, recommendations or decisions that can influence physical or virtual environments. Read the elements together: a deterministic rules engine someone wrote by hand does not infer, and a model that only a researcher ever runs is not placed on the market.

  • Machine-based, and designed to operate with varying levels of autonomy.
  • May exhibit adaptiveness after deployment: it can keep changing once it runs.
  • Infers, from input, how to generate outputs. This is the element that does most of the work.
  • Outputs are predictions, content, recommendations or decisions.
  • Those outputs can influence physical or virtual environments.

Worth knowing The Commission has published guidelines on this definition. They are its interpretation, they are not binding, and a court is not bound by them. Where they matter here, they are labeled.

The model and the system are different objects

A general-purpose AI model is the trained artifact: Article 3(63) describes a model that displays significant generality and can competently perform a wide range of distinct tasks. A general-purpose AI system, in Article 3(66), is a system based on such a model that can serve a variety of purposes. The distinction decides who owes what: Chapter V binds whoever provides the model, while the system you assemble on top is classified like any other system, by what it is used for.

Whether it reaches you

Who the Regulation binds

Article 2(1) lists the parties in scope. Two of its rows catch teams that assume the Regulation is somebody else’s problem: a deployer established in the Union is bound even when the system came from a vendor, and a provider or deployer in a third country is bound when the output produced by the system is used in the Union.

Party In scope when
Provider It places an AI system on the market or puts it into service in the Union, or places a general-purpose AI model on the Union market, wherever the provider itself is established.
Deployer It has its place of establishment, or is located, within the Union.
Provider or deployer in a third country The output produced by the AI system is used in the Union.
Importer and distributor It brings an AI system to, or makes it available on, the Union market.
Product manufacturer It places a product on the market together with an AI system, under its own name or trademark.
Authorised representative It acts for a provider not established in the Union.
Affected persons They are located in the Union.

Where the Regulation does not reach

The exclusions are narrower than they are usually quoted. Each one is a carve-out for an activity, not for a kind of company, and two of them stop the moment a system reaches the market.

  • Military, defence or national security purposes, regardless of the type of entity carrying out those activities (Art. 2(3)).
  • Systems and models developed and put into service for the sole purpose of scientific research and development (Art. 2(6)).
  • Research, testing or development activity prior to placing on the market or putting into service. Testing in real-world conditions is not covered by that exclusion (Art. 2(8)).
  • Deployers who are natural persons using a system in a purely personal non-professional activity (Art. 2(10)).
  • Systems released under free and open-source licences, unless they are placed on the market or put into service as high-risk systems or as systems falling under Article 5 or Article 50 (Art. 2(12)).

This Regulation does not replace data protection law

Article 2(7) keeps Union law on the protection of personal data, privacy and the confidentiality of communications fully applicable to personal data processed in connection with the rights and obligations laid down here. The two regimes meet in specific places rather than merging: a deployer uses the Article 13 information to carry out its GDPR data protection impact assessment, and a fundamental rights impact assessment may cross-reference that assessment where it already covers the same ground.

Which role you are in

The roles, and what puts you in one

The Regulation does not ask what kind of company you are. It asks what you did with a particular system. Every duty in the Act hangs off one of these roles, and the two that matter for most engineering teams are provider and deployer.

Role What puts you in it Defined in
Provider You develop a system or a general-purpose AI model, or have one developed, and place it on the market or put it into service under your own name or trademark. Payment is irrelevant. Art. 3(3)
Deployer You use a system under your own authority, outside a personal non-professional activity. Art. 3(4)
Importer You are in the Union and place on the market a system bearing the name or trademark of a person established in a third country. Art. 3(6)
Distributor You are in the supply chain, other than provider or importer, and make a system available on the Union market. Art. 3(7)
Authorised representative You are in the Union and hold a written mandate from a provider to carry out its obligations. Art. 3(5)

One system at a time, one role at a time

The role attaches to a system, not to a company. Article 3(3) makes you a provider of the system you place on the market; Article 3(4) makes you a deployer of the system you use under your own authority. The same team is routinely both: provider of the product it sells, deployer of the vendor tools it runs internally. Answer the question once per system, and answer it in the role you hold for that system, or the obligations you read will belong to somebody else.

When your role moves

Article 25 turns a distributor, importer, deployer or any other third party into the provider of a high-risk system, with the provider obligations of Article 16, in three circumstances. The change is not theoretical for a platform team: putting your brand on a bought system, or changing what a system is for, is a normal Tuesday.

  • You put your name or trademark on a high-risk system already on the market (Art. 25(1)(a)).
  • You make a substantial modification to a high-risk system already on the market, and it stays high-risk (Art. 25(1)(b)).
  • You modify the intended purpose of a system that was not high-risk, including a general-purpose AI system, so that it becomes high-risk (Art. 25(1)(c)).

Worth knowing When that happens, the initial provider stops being the provider of that system, and must cooperate: technical documentation, known limitations and failure modes, and targeted technical access for testing and validation (Art. 25(2)).

Where your system lands

How the Act sorts what you run

The pyramid every explainer draws is a teaching aid, not the structure of the Regulation. What the text actually does is create separate regimes that can stack on the same system: a high-risk system that talks to people owes the Chapter III requirements and the Article 50 disclosure, and a system that is none of these still owes Article 4.

What the Act does Where What it means for you
Prohibits a practice outright Art. 5 No compliance route exists. The practice is banned.
Classifies a system as high-risk through a product route Art. 6(1), Annex I The system is a safety component of a product, or a product, covered by Annex I harmonisation legislation and needing third-party conformity assessment.
Classifies a system as high-risk through a use-case route Art. 6(2), Annex III The use case is listed in Annex III, unless the Article 6(3) derogation applies and is documented.
Imposes disclosure duties Art. 50 Interaction, synthetic content, emotion recognition and biometric categorisation, deep fakes. These stack on top of any other tier.
Binds a general-purpose AI model Chapter V Duties on whoever provides the model, and more of them once the model has systemic risk. Not a risk classification of a system.
Everything else Art. 4 No tier-specific duty, but providers and deployers still owe AI literacy measures.

Worth knowing Regime and risk are different axes, which is why this site facets them separately: Chapter IV is named for an obligation type and Chapter V for a subject type, neither for a level of risk.

The Annex III filter, and the trapdoor in it

A system whose use case is listed in Annex III is high-risk by default. Article 6(3) lets it out only where it does not pose a significant risk of harm to health, safety or fundamental rights, including by not materially influencing the outcome of decision making, and only where one of four conditions holds. The derogation is not self-service: a provider who relies on it documents the assessment before the system is placed on the market, and registers the system.

  • The system performs a narrow procedural task.
  • It improves the result of a previously completed human activity.
  • It detects decision-making patterns or deviations from them, and is not meant to replace or influence the previously completed human assessment without proper human review.
  • It performs a preparatory task to an assessment relevant to an Annex III use case.

Worth knowing A system that performs profiling of natural persons is always high-risk. The filter never opens for it.

The product route, and what the amendment clarified

Article 6(1) makes a system high-risk when it is a safety component of a product, or is itself a product, covered by the Annex I harmonisation legislation, and that product must undergo third-party conformity assessment. The amended text draws the line more sharply than the original did: systems used solely for non-safety aspects of user assistance, performance optimisation, service efficiency, automation, convenience or quality control do not qualify as safety components, while systems whose failure or malfunctioning would endanger health and safety do.

Applies from Deferred 2 Aug 2028 EU Art. 6(1), (1a), (1b), (1c) EU Annex I

The disclosure duties stack on whatever else applies

Article 50 is not a tier below high-risk. It is a separate set of duties that lands on providers and deployers of ordinary systems, and on high-risk ones too. Which of them you owe depends on your role, not on a risk score.

Duty Who owes it Where
Tell people they are interacting with an AI system, unless that is obvious Provider Art. 50(1)
Mark synthetic audio, image, video or text in a machine-readable format, detectable as artificially generated or manipulated Provider Art. 50(2)
Inform the people exposed to an emotion recognition or biometric categorisation system Deployer Art. 50(3)
Disclose that image, audio or video content is a deep fake, and that published text on matters of public interest is artificially generated Deployer Art. 50(4)

The tier nobody talks about: everything else

Most systems a product company runs are in none of the tiers above. They still carry one duty. Article 4 makes providers and deployers take measures to support the AI literacy of their staff and of other people operating or using the systems on their behalf, in proportion to their technical knowledge and the context of use. It does not require guaranteeing any specific level of literacy in any individual, and it is the first obligation in this Regulation that became applicable.

Applies from In force 2 Feb 2025 EU Art. 4 EU Art. 113(a)

Models, open weights and who carries what

Open models and general-purpose models, by what you actually do

Chapter V binds the provider of a model, and the word provider does a lot of work. Find the row that matches what your team does with the weights, not the row that matches the logo on the model card.

What you do What you carry Where
You train and release a general-purpose AI model Technical documentation of the model, information and documentation for downstream providers, a copyright policy, and a public summary of training content Art. 53(1)(a) to (d)
You serve someone else’s model unmodified Nothing new at the model level. You are building a system on it, so the system is classified on its own use case Art. 3(66), Art. 6
You call a model through an API Same: the model duties stay with the model provider, and you answer for the system you built Art. 3(3), Art. 6
You fine-tune a model Possibly the model-provider duties, for the modification. The Commission reads a modification using more than a third of the original training compute as the indicative threshold Art. 53, and the Commission guidelines
You release the model under a free and open-source licence The Article 53(1)(a) and (b) duties do not apply, if the licence allows access, use, modification and distribution and the parameters, architecture and usage information are public. The copyright policy and the training-content summary still apply Art. 53(2)
Your model crosses the systemic-risk threshold The Article 55 duties on top, and the open-source exception no longer applies Art. 51, Art. 55
You are established outside the Union An authorised representative in the Union Art. 54

Worth knowing The one-third-of-compute figure is an indicative criterion from the Commission’s guidelines, not a threshold in the Regulation. It is interpretation, it is not binding, and it may move.

When you become a provider

Two different doors lead to the same place, and a team that self-hosts open weights can walk through either without noticing. At the model level, modifying a general-purpose AI model can make you the provider of the modified model, with the Chapter V duties for it. At the system level, Article 25 makes you the provider of a high-risk system if you put your name on it, substantially modify it, or change its intended purpose so that it becomes high-risk. Neither door asks whether you paid for the model.

  • Model level: your modification carries the Chapter V duties for what you changed. The Commission’s indicative criterion is more than a third of the original training compute.
  • System level: Article 25(1) moves the provider obligations of Article 16 onto you.
  • The exemption for free and open-source models never covers a model with systemic risk, and Article 2(12) never covers a system placed on the market as high-risk or under Article 5 or Article 50.

Worth knowing The compute criterion comes from Commission guidelines and is not binding. The Article 25 and Article 53(2) rules are in the Regulation itself.

What happens if you get it wrong

What the ceilings actually are

Article 99 sets maximums, not tariffs. Each row is a ceiling on what a Member State authority may impose, and for an undertaking the rule is the higher of the fixed amount and the percentage of total worldwide annual turnover for the preceding financial year. The numbers in circulation are often the ones from the 2021 proposal, which were different.

Infringement Ceiling Where
A prohibited practice under Article 5 EUR 35 000 000, or 7 % of total worldwide annual turnover, whichever is higher Art. 99(3)
Obligations of providers, authorised representatives, importers, distributors, deployers, notified bodies, and the Article 50 transparency duties EUR 15 000 000, or 3 % of total worldwide annual turnover, whichever is higher Art. 99(4)
Supplying incorrect, incomplete or misleading information to notified bodies or national competent authorities EUR 7 500 000, or 1 % of total worldwide annual turnover, whichever is higher Art. 99(5)
A provider of a general-purpose AI model, fined by the Commission rather than a Member State EUR 15 000 000, or 3 % of annual total worldwide turnover, whichever is higher Art. 101(1)

If you are an SME or an SMC, the rule inverts

This is the paragraph that matters most to a company of five to fifty engineers, and the one most often quoted wrongly. For SMEs, including start-ups, each fine referred to in Article 99 is up to the percentage or the amount of paragraphs 3, 4 and 5, whichever is lower. For small mid-cap enterprises the same lower-of-the-two rule applies, but only to the fines in paragraphs 4 and 5. Article 99(1) also tells Member States to take the interests of SMEs, start-ups and SMCs, and their economic viability, into account when imposing penalties.

Worth knowing Sources that state "the higher of" as a universal rule are describing paragraphs 3 to 5 without their exception.

Who fines, and since when

The Regulation does not fine anyone by itself. Article 99(1) makes Member States lay down the rules on penalties and other enforcement measures, effective, proportionate and dissuasive, and notify them to the Commission. So the authority that can fine your company is national, and the national regime is where the detail lives. The chapter that carries these rules has been applicable since the date Article 113(b) sets, with Article 101 excepted from that block.

Applies from In force 2 Aug 2025 EU Art. 99(1), (2) EU Art. 113(b)

Scenarios

Typical systems, read against the Act's own categories. Each one names the provision that decides the answer and what would change it.

A code assistant for your own engineers

Illustrative Reading still settling

An assistant suggests code in the editor and opens pull requests, running against a hosted model.

Your role
ProviderDeployer
Where it lands
Not classified In force 2 Aug 2026
Decided by
No Annex III use case. The open question is Article 50(2), because the assistant generates text.

What you have to be able to produce

  • Content marking in the generation pipeline
  • Onboarding notes for AI-touching roles
  • Provenance-preservation test in CI
  • Team enablement plan for people operating AI systems

What would change the answer

  • Article 50(2) does not apply to the extent a system performs an assistive function for standard editing or does not substantially alter the input data or its semantics. Whether a generated patch is assistive editing is exactly the line this exemption draws, and it is not settled.
  • Generated code that ships inside a product covered by Annex I harmonisation legislation is a question about that product, not about the assistant.
  • Use it to evaluate engineers rather than to help them and Annex III point 4(b) applies.

A credit-decision feature

Illustrative

A model scores applicants for a lending product and the score drives the decision, with a human able to override it.

Your role
ProviderDeployer
Where it lands
High risk Deferred 2 Dec 2027
Decided by
Annex III, point 5(b): systems intended to evaluate the creditworthiness of natural persons or establish their credit score, with the exception of systems used to detect financial fraud.

What you have to be able to produce

  • Adversarial and injection test suite
  • Annex IV technical file
  • Bias examination report
  • Conformity route decision per system
  • Dataset cards with provenance
  • Decision factors captured per output
  • Decision-correlation IDs across services
  • Declared accuracy levels and metrics
  • Deployer-side log retention
  • Deployment instructions record per system
  • Doc generation wired into CI
  • Documentation format decision on record
  • Escalation path for emergent risk
  • Explanation request process
  • Field-risk signal feed into the register
  • Foreseeable-misuse analysis per release
  • Fundamental rights impact assessment
  • Inference event schema
  • Kill switch and override, with tests
  • Living risk register with review cadence
  • Model performance SLOs with alerts
  • Named oversight roles
  • Oversight runbook
  • Oversight UX with override path
  • Per-run lineage records
  • Registration entries per system
  • Replay runbook
  • Representativeness note for the target population
  • Risk-to-control mapping in the design docs
  • Scope determination on record
  • Stated assumptions per data set
  • Tamper-evident log storage
  • Worker information notice

What would change the answer

  • Unlike the hiring case, this one carries a fundamental rights impact assessment: Article 27(1) names Annex III point 5(b) explicitly.
  • Restricting the system to fraud detection takes it out of point 5(b). Scoring the same people for a lending decision puts it back.
  • An affected person can ask for an explanation of the individual decision under Article 86, and that explanation comes from the same records Article 12 asked you to keep.

A customer-support chatbot on your public site

Illustrative

The same stack, pointed outward: a chatbot that answers customer questions, drafts replies and escalates to a human when it cannot answer.

Your role
ProviderDeployer
Where it lands
Any risk level In force 2 Aug 2026
Decided by
Article 50(1): a system intended to interact directly with natural persons. The transparency duties attach without the system being high-risk.

What you have to be able to produce

  • Content marking in the generation pipeline
  • Disclosure pattern in the design system
  • Onboarding notes for AI-touching roles
  • Provenance-preservation test in CI
  • Reusable disclosure component
  • Team enablement plan for people operating AI systems

What would change the answer

  • If the bot decides access to an essential service rather than describing it, Annex III point 5 puts it in the high-risk tier.
  • Article 50(2) marking has an exemption where the system performs an assistive function for standard editing or does not substantially alter the deployer’s input. A bot that writes the answer is not editing yours.
  • Publishing its text as an article on a matter of public interest brings Article 50(4) into play, and that duty sits on the deployer.

A CV-screening feature in your product

Illustrative

You are about to ship a feature that ranks and filters job applications for the companies that use your hiring product.

Your role
ProviderDeployer
Where it lands
High risk Deferred 2 Dec 2027
Decided by
Annex III, point 4(a): systems intended to be used for the recruitment or selection of natural persons, in particular to analyse and filter job applications and to evaluate candidates.

What you have to be able to produce

  • Adversarial and injection test suite
  • Annex IV technical file
  • Authority notification runbook
  • Bias examination report
  • Conformity route decision per system
  • Dataset cards with provenance
  • Decision-correlation IDs across services
  • Declared accuracy levels and metrics
  • Doc generation wired into CI
  • Documentation format decision on record
  • Escalation path for emergent risk
  • EU declaration of conformity per system
  • Field-data review cadence
  • Field-risk signal feed into the register
  • Foreseeable-misuse analysis per release
  • Incident classification with regulatory branch
  • Inference event schema
  • Instructions for use per system
  • Kill switch and override, with tests
  • Living risk register with review cadence
  • Model performance SLOs with alerts
  • Named reporting roles
  • Output metadata deployers can read
  • Oversight runbook
  • Oversight UX with override path
  • Per-run lineage records
  • Post-market monitoring plan
  • Registration entries per system
  • Replay runbook
  • Representativeness note for the target population
  • Resource, lifetime and maintenance inputs for the instructions
  • Restore test on aged logs
  • Retention budget and DPO sign-off
  • Retention policy meeting the six-month floor
  • Risk-to-control mapping in the design docs
  • Stated assumptions per data set
  • Tamper-evident log storage
  • Versioned field telemetry

What would change the answer

  • The Article 6(3) derogation is the only way out, and a system that performs profiling of natural persons never qualifies. Ranking candidates is hard to argue as a narrow procedural task.
  • Your customers are deployers of this system and carry Article 26 duties, including keeping the logs under their control and telling candidates they are subject to it.
  • A customer who puts its own brand on your feature becomes its provider under Article 25(1)(a), and you stop being it.

A product recommender in your storefront

Illustrative

A model ranks what each visitor sees, trained on browsing and purchase history.

Your role
ProviderDeployer
Where it lands
Not classified In force 2 Feb 2025
Decided by
Ranking products is not an Annex III use case and not a safety component. What the system infers about people is what to watch.

What you have to be able to produce

  • Onboarding notes for AI-touching roles
  • Team enablement plan for people operating AI systems

What would change the answer

  • Price or risk-assess life and health insurance with it and Annex III point 5(c) applies; score creditworthiness and point 5(b) does.
  • Article 5 prohibits certain manipulative and exploitative practices outright. A recommender tuned to exploit the vulnerabilities of a specific group is a different object from one tuned to relevance.
  • Profiling turns the Article 6(3) escape hatch off for any Annex III system, so it matters what the model infers, not only what it displays.

A RAG assistant over internal documents, on a vendor model

Illustrative

You wrapped a vendor model in a retrieval layer over your own wiki and runbooks, and put it in front of your own staff. Nobody outside the company can reach it.

Your role
ProviderDeployer
Where it lands
Not classified In force 2 Feb 2025
Decided by
No Annex III use case, and not a safety component under Article 6(1). Putting a system into service for your own use still makes you its provider under Article 3(11).

What you have to be able to produce

  • Disclosure pattern in the design system
  • Onboarding notes for AI-touching roles
  • Reusable disclosure component
  • Team enablement plan for people operating AI systems

What would change the answer

  • Point it at a decision the Act lists. The moment it screens candidates or scores people, Annex III applies and the answer changes completely.
  • Article 50(1) asks you to tell people they are interacting with an AI system unless that is obvious. For an internal assistant behind a login it usually is; write down why you concluded that.
  • Fine-tune the vendor model and you may become the provider of the modified model, with Chapter V duties for it.

An open model, fine-tuned and sold inside your product

Illustrative Reading still settling

You took an open-weight model, fine-tuned it on your own data, and it now powers a paid feature in the product you sell.

Your role
Provider
Where it lands
Not classified In force 2 Aug 2025
Decided by
Chapter V, as the provider of the modified model, and separately whatever Article 6 says about the system you built on it.

What you have to be able to produce

  • Downstream information pack
  • Model documentation
  • Onboarding notes for AI-touching roles
  • Provider-status assessment for fine-tunes
  • Public training-content summary
  • Team enablement plan for people operating AI systems
  • Written mandate for the model's authorised representative

What would change the answer

  • The Article 53(2) exception covers models released under a free and open-source licence with public parameters, architecture and usage information, and it never covers a model with systemic risk.
  • Recital 103 reads components provided against a price or otherwise monetised as outside the free and open-source exceptions. A recital is interpretive context, not operative law, and it is the weakest link in this row.
  • Crossing the Article 51 systemic-risk threshold adds the Article 55 duties and removes the exception entirely.

An open-weight model on your own cluster, serving an internal copilot

Illustrative

You pulled open weights, you serve them on your own Kubernetes cluster, and an internal copilot calls them. Nothing leaves your network, and you control every log.

Your role
DeployerProvider
Where it lands
Not classified In force 2 Feb 2025
Decided by
The model is a general-purpose AI model, which the risk taxonomy does not classify at all. The copilot is the system, and it matches no Annex III use case.

What you have to be able to produce

  • Disclosure pattern in the design system
  • Onboarding notes for AI-touching roles
  • Reusable disclosure component
  • Team enablement plan for people operating AI systems

What would change the answer

  • Fine-tune the weights and you may become the provider of the modified model. The Commission’s indicative criterion is a modification using more than a third of the original training compute, which is guidance, not a threshold in the Regulation.
  • Article 2(12) puts systems released under free and open-source licences outside the Regulation, but never when they are placed on the market as high-risk or under Article 5 or Article 50.
  • Because you run the model, the logs are under your control, which is the fact that decides who answers Article 19 or Article 26(6) if the system ever becomes high-risk.

What this page does not do

It does not classify your system, and it cannot. Classification turns on facts about your product, your users and how the system reaches the market. What it can do is show you which question decides the answer, and where the text answers it.

Then go one layer down

The explorer holds every obligation faceted by role and date. The engineering view groups them by the platform capability they demand. The law is the primary text, with the amendment marked inline.

Explorer → Engineering → The law → Timeline →