FAQEU

EU AI Act Does this tool count as AI?

Check how the tool works before assigning AI Act duties. Software that infers how to produce an output can qualify; software that only runs fixed human-written rules may fall outside the definition.

Then identify the model or system, its intended use, the EU connection and each organisation's role.

Author
Sorena AI
Published
May 9, 2026
Updated
Oct 21, 2026
Overview

Start with Article 3(1), the legal definition of an . Describe what the tool does and how it produces outputs. Then check whether you are assessing a model, a standalone system or an embedded component, and who supplies or uses it in the EU. Keep the technical and commercial evidence behind your conclusion.

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4 of 4 questions
Question 1

Does rules-based software count as AI?

An is machine-based, operates with some autonomy and infers from inputs how to generate outputs. Those outputs can include predictions, content, recommendations or decisions that influence a physical or virtual environment. Check all parts of Article 3(1), including explicit or implicit objectives and the possibility of adaptation after deployment.

A tool is less likely to be an when it only executes rules defined solely by people, such as fixed validation checks, deterministic routing tables, hard-coded eligibility rules, or ordinary calculations with no learning, reasoning, modelling, or inference beyond basic data processing.

Use Article 3(1) and Recital 12 to classify the actual system. The Commission's definition guidelines explain its interpretation; they do not replace the legal definition. Keep evidence of how the tool infers its outputs. A supplier label such as AI-powered or automated does not settle the question.

  • Record the inputs, objective, output type, autonomy level, and whether the system derives a model, algorithm, recommendation, prediction, content, or decision from data or encoded knowledge.
  • Separate deterministic automation from inference: a manually written rule that always produces the same result from the same fields is not enough by itself.
  • Treat logic- and knowledge-based systems as possible AI systems when they infer from encoded knowledge or symbolic representations, even without machine learning.
  • Keep the intended-purpose evidence from instructions, sales material, product specifications, and technical documentation because Article 6 high-risk classification depends on purpose and use context.

Does simple rules-based software count as AI?

Usually no, if the software is based only on rules defined by people to automatically execute operations. Recital 12 says the definition should not cover simpler traditional software or programming approaches based solely on human-defined rules. Escalate the case when the rules engine also learns, reasons, models, ranks, recommends, predicts, or otherwise infers from inputs or encoded knowledge.

Does inference require machine learning?

No. Inference can use machine learning or logic- and knowledge-based methods that reason from encoded knowledge or symbolic representations. Check whether the system infers how to generate outputs for an explicit or implicit objective.

Question 2

Is it a model, a system or a product component?

Keep separate records for the (GPAI model) and the built with it. The model supplies reusable capabilities. The system uses those capabilities for an . A company that integrates the model into its own system can have system-provider duties for that integration.

Embedded and product-linked cases need two checks. First, decide whether the AI component itself is an . Second, decide whether Article 6 makes it high-risk because it is a safety component, is itself a covered product, or falls into an Annex III use case.

Apply the amended safety-component tests in Regulation (EU) 2026/1744. A safety function has the of preventing or mitigating health and safety risks. Solely non-safety user assistance, optimisation, efficiency, automation, convenience, or quality control does not qualify, but a failure or malfunction that would endanger health and safety still does. A product assessment required solely for non-health-and-safety risks, such as spectrum distribution or electromagnetic interference without a health-and-safety effect, does not satisfy Article 6(1)(b).

  • For GPAI, identify the model, the provider placing the model on the Union market, and any downstream provider integrating it into a specific .
  • For embedded software, document whether the is physically integrated into the product or serves product functionality without being physically integrated.
  • For product safety cases, check whether the is a safety component of a product or is itself a product covered by Annex I legislation and subject to third-party conformity assessment.
  • For Annex III cases, match the exact listed use case. To rely on Article 6(3), establish no significant risk of harm, at least one listed condition, and no profiling of natural persons. Conditions cover a narrow procedural task, improvement of completed human work, properly reviewed decision-pattern detection, or preparation for the listed assessment; document and register the conclusion.

Is a the same as an ?

No. Article 3 separately defines a and a general-purpose . A GPAI model displays significant generality and can be integrated into downstream systems or applications. A general-purpose AI system is an AI system based on a GPAI model and capable of serving a variety of purposes. The classification record should therefore identify the model, the system built from it, and the actor responsible for each.

When is embedded AI high-risk?

An embedded AI component can be high-risk when Article 6(1) applies: the is intended as a safety component of a product, or is itself a product, covered by Annex I Union harmonisation legislation and that product or system must undergo third-party conformity assessment. Separately, an embedded or non-embedded AI system can be high-risk if its intended use is listed in Annex III.

Question 3

Does the EU connection or your role change the answer?

The Act can cover providers outside the EU when they place AI systems or general-purpose AI models on the EU market. It can also cover non-EU providers or deployers whose system outputs are used in the EU. Article 2 separately addresses EU deployers, importers, distributors, product manufacturers, authorised representatives and affected people in the EU.

Role classification is fact-specific and can change after launch. A distributor, importer, deployer, or other third party can become the provider of a if it puts its name or trademark on the system, substantially modifies it, or changes the so that the system becomes high-risk.

Scope exclusions also matter. The Regulation contains specific exclusions for personal non-professional use, certain scientific research and development activity, pre-market research, testing or development that respects applicable Union law, and some free and open-source releases. Those exclusions have conditions and do not create a general exemption for commercial deployment, prohibited practices, high-risk systems, or Article 50 uses. The Article 2(8) pre-market exclusion does not cover testing in real-world conditions.

  • Map the market path: who develops, brands, imports, distributes, deploys, integrates, or productizes the system or GPAI model.
  • Record the EU connection: Union market placement, Union putting into service, EU establishment or location of the deployer, Union use of outputs, or affected persons located in the Union.
  • Check whether a supplier answer covers only the model, only the , only the deployment, or the product into which the system is integrated.
  • Reclassify after material changes to , branding, integration, safety function, user population, EU market availability, or human-impacting use case.

Can a non-EU provider be covered?

Yes. Article 2 covers providers placing AI systems or GPAI models on the Union market regardless of whether the provider is in the Union or a third country. It also covers providers and deployers in a third country where the output produced by the is used in the Union.

Can a deployer or distributor become the provider?

Yes. For a system already placed on the market or put into service, Article 25 can transfer provider duties when a third party puts its name or trademark on a high-risk system, substantially modifies it while it remains high-risk, or changes a non-high-risk system's so that it becomes high-risk. The branding trigger is without prejudice to contractual arrangements allocating the obligations differently. Record which trigger applies; a technical update alone does not prove .

Does an open-source licence create an exemption?

Not always. Article 2(12) excludes AI 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 covered by Article 5 prohibited practices or Article 50 transparency duties. The licence label therefore does not remove those categories or decide whether a commercial actor has placed the system on the market.

Is purely private use covered?

The Regulation does not apply to deployer obligations where a natural person uses an in a purely personal, non-professional activity. That exclusion is limited to the person's deployer obligations; it does not remove obligations that apply to the provider or another operator placing the system on the Union market.

Question 4

What evidence should you keep?

Keep enough evidence for someone else to repeat the classification. Identify the software, model or system assessed; why it meets or falls outside the AI definition; its ; the EU connection; each actor's role; and the high-risk checks completed.

For high-risk and near-high-risk cases, align the evidence with Annex IV-style system description fields even if the team is still at classification stage: interactions with other hardware or software, form of supply, product integration, development methods, third-party components, output quality, monitoring, limits, and lifecycle changes.

  • definition evidence: autonomy, inputs, objectives, output type, inference method, model or algorithm derivation, and why simple human-defined rules are or are not enough to describe the tool.
  • GPAI evidence: model identity, model provider, downstream system provider, integration method, tasks the model can perform, and system-specific .
  • High-risk evidence: Article 6(1) product-safety check, Annex III use-case check, any Article 6(3) not-high-risk rationale, and profiling status.
  • Role and scope evidence: provider, deployer, importer, distributor, product manufacturer, authorised representative, EU market or output-use facts, branding, substantial modifications, and intended-purpose changes.
  • Change evidence: version history, technical modifications, deployment context changes, supplier changes, instructions for use, and the date and approver of each reclassification.
Primary sources

References and citations

eur-lex.europa.eu5 citations
Referenced sections
  • Primary legal text supporting AI system definitions, territorial scope, operator roles, high-risk classification, GPAI definitions, value-chain responsibility changes, and Annex IV evidence fields.
  • Supports the Article 3 AI system definition and Recital 12 distinction between inference-based AI and simpler human-defined rule execution.
  • Supports the separate definitions for AI systems, general-purpose AI models, general-purpose AI systems, safety components, and Article 6 high-risk classification.
Show 2 more
  • Supports Article 2 territorial scope, Article 3 operator definitions, and Article 25 role changes along the AI value chain.
  • Supports the evidence fields from Article 3 definitions, Article 6 classification documentation, Article 25 role changes, and Annex IV technical-documentation content.
"AI system"
More quoted passages
"infers, from the input it receives"
"general-purpose AI model"
"placing on the market"
"technical documentation"
ai-act-service-desk.ec.europa.eu3 citations
Referenced sections
  • Official AI Act Service Desk article page for high-risk classification under Article 6, including product-linked and Annex III screening.
  • Official article page for the high-risk classification rules used to screen product-linked and Annex III edge cases.
  • Supports keeping a documented high-risk or not-high-risk assessment for Annex III edge cases.
"high-risk"
More quoted passages
"Classification rules"
digital-strategy.ec.europa.eu2 citations
Referenced sections
  • Commission guidance page used for GPAI provider-scope context and the distinction between model-provider obligations and downstream AI-system integration.
  • Supports the distinction between GPAI model-provider scope and downstream AI ecosystem roles.
"GPAI models"
More quoted passages
"general-purpose AI models"
digital-strategy.ec.europa.eu2 citations
Referenced sections
  • Commission FAQ used for public explanation of AI Act scope, risk-based classification, high-risk examples, product safety links, deployer obligations, and GPAI context.
  • Commission FAQ source explaining that the framework applies to public and private actors inside and outside the EU in relevant market or use scenarios.
"risk-based approach"
More quoted passages
"inside and outside the EU"
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