EU AI ActOverview

EU AI Act (Regulation (EU) 2024/1689) Requirements overview

The Act routes systems and models into obligation sets. Compliance starts with correct routing.

This page summarizes the four main requirement tracks and the evidence each one drives.

Author
Sorena AI
Published
Mar 4, 2026
Updated
Mar 4, 2026
Sections
4

Structured answer sets in this page tree.

Primary sources
4

Cited legal and guidance references.

Publication metadata
Sorena AI
Published Mar 4, 2026
Updated Mar 4, 2026
Overview

A good AI Act implementation begins with a simple question: which requirement track applies to this system or model? The Regulation is not one flat checklist. It imposes different obligations depending on whether the system is prohibited, high risk, subject to transparency duties, or connected to GPAI provider obligations.

Section 1

Track one: prohibited practices

If Article 5 applies, the correct operational outcome is prevention. These are not use cases you mitigate into compliance through documentation alone. Product and procurement teams need an active gate that screens for manipulation, exploitation of vulnerability, social scoring, prohibited biometric practices, and other listed categories.

Because Article 5 infringements carry the highest penalties, this track should be visible at executive level.

  • Key output: screening record and stop or redesign decision.
  • Key owners: product, legal, risk, security.
  • Key evidence: use case rationale, user journey, data and biometric review.
  • Key review timing: intake, procurement, and material changes.
Section 2

Track two: high risk systems

High risk obligations apply through the product safety route in Article 6(1) or the Annex III route in Article 6(2). Once a system is high risk, the provider and deployer evidence standard increases sharply. Articles 9 to 15 set the technical and organizational core, but the surrounding duties on conformity, registration, monitoring, retention, and user information matter just as much.

This track is where most enterprise implementation work sits because it touches architecture, data governance, testing, human oversight, and post market operations.

  • Key output: Annex IV aligned technical documentation and control evidence.
  • Key owners: provider, deployer, engineering, risk, quality, operations.
  • Key evidence: risk management, data governance, logging, oversight, accuracy, cybersecurity, FRIA where applicable.
  • Key review timing: design, pre release, and post market monitoring.
Section 3

Track three: transparency duties

Article 50 creates obligations where natural persons interact directly with AI systems, where synthetic outputs must be machine readable and detectable, where emotion recognition or biometric categorisation systems are used, and where deepfakes or certain AI generated text are deployed. This work belongs inside product, design, accessibility, editorial, and QA processes.

Transparency is not solved by a generic footer. The notice has to appear in the right interface, at the right moment, and often with technical marking or logging behind it.

  • Key output: disclosure and marking design across product surfaces.
  • Key owners: product, design, content, engineering, QA.
  • Key evidence: copy library, screenshots, machine readable marking logic, and display logs.
  • Key review timing: feature design, release, and model or content pipeline changes.
Section 4

Track four: GPAI provider obligations

Chapter V applies to providers of general purpose AI models. It requires model level technical documentation, downstream documentation, a copyright policy, and a public summary of training content. Systemic risk adds compute threshold monitoring, notification, mitigation, and serious incident response expectations.

Even organizations that are not GPAI providers need to understand this track because they often depend on upstream model suppliers for evidence and contractual support.

  • Key output: Article 53 to 55 artifact set and supplier evidence model.
  • Key owners: model provider, legal, security, documentation, operations.
  • Key evidence: training content summary, copyright policy, technical documentation, notification and incident records.
  • Key review timing: before market placement, on major model changes, and during systemic risk monitoring.
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References and citations

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