Making Available

Under EU AI Act Article 3(14), Making Available is the supply of an AI system for distribution or use on the Union market in the course of a commercial activity, whether in return for payment or free of charge. It is broader than Placing on the Market, covering all subsequent distributions after initial market entry, and triggers compliance obligations for distributors, providers, and authorised representatives throughout the AI value chain.

Semantic Classification

Content

• The supply of an AI system for distribution or use on the Union market in the course of a commercial activity, whether in return for payment or free of charge.

  Source

  Primary: EU AI Act Article 3(14) Context: Supply chain actor definition

  Regulatory Context

  “Making available” is a broader concept than “placing on the market.” It encompasses all subsequent distributions after initial market entry and defines obligations for distributors in the AI value chain.

  Key Characteristics

  Commercial Activity

  • Business context: Not personal non-professional use

  • Economic nature: Part of commercial operation

  • Payment agnostic: Whether paid or free

    Distribution or Use Supply

  • Distribution: Onward supply to others (distributor role)

  • Use: Providing access for deployment (may involve deployers)

    Union Market

  • EEA scope: EU 27 + Norway, Iceland, Liechtenstein

  • Single market: Free movement principle applies

    Actors Making Available

    1. Distributors (Article 24)

    Supply AI systems after initial placing on market:

  • Resellers

  • Wholesalers

  • Platform marketplaces

  • Retail channels

    Not the original provider/importer

    2. Providers (Ongoing Supply)

    Continued distribution after initial placing:

  • Software updates

  • New versions

  • Subscription renewals

    3. Authorised Representatives (Article 22)

    On behalf of non-EU providers:

  • Liaison with authorities

  • Compliance verification

  • Documentation provision

    Obligations When Making Available

    For Distributors of High-Risk AI (Article 24)

    Before Making Available

    1. Verify CE marking present (Article 24(1))

    2. Check required documentation accompanies system:

    • Instructions for use

    • EU Declaration of Conformity 3. Verify provider/importer identification 4. Assess compliance indicators:

    • No obvious non-compliance signs

    • System appears conforming

      If Non-Compliance Suspected (Article 24(2))

  • Do not make available until compliance achieved

  • Inform provider/importer of concerns

  • Notify market surveillance authority if serious non-compliance

    During Making Available (Article 24(3))

  • Storage and transport conditions: Preserve compliance

  • Traceability: Maintain supply chain records

  • Cooperation: Respond to authority requests

    For All Actors

  • Market surveillance cooperation (Article 25)

  • Documentation provision upon request

  • Sample provision if required

  • Corrective action support

    Source

    Primary: EU AI Act Article 3(14) Context: Supply chain actor definition

    Regulatory Context

    “Making available” is a broader concept than “placing on the market.” It encompasses all subsequent distributions after initial market entry and defines obligations for distributors in the AI value chain.

    Related Concepts

• Placing on the Market (AI-0124): Initial market entry

  • Putting into Service (AI-0126): Deployment for use

  • Distributor (AI-0130): Key actor making available

  • Importer (AI-0129): Third-country making available

    Due Diligence for Distributors

    Recommended Checks

    1. CE marking verification: Authentic, properly affixed
    2. Documentation review: Instructions, declaration complete
    3. Provider identification: Verify legitimate provider
    4. System functionality: Basic operability check
    5. Red flags: Look for obvious non-compliance indicators

    Risk-Based Approach

    Higher scrutiny for:

  • New providers

  • Third-country imports

  • High-risk use cases (Annex III)

  • Complex AI systems

    See Also

  • EU AI Act Article 3(14), Article 24 (Distributor Obligations)

  • Market Surveillance Regulation (EU) 2019/1020

  • Digital Services Act (EU) 2022/2065 (Platform obligations)

  • Blue Guide on Product Rules 2022 (EU product safety guidance)

    Academic Context

• Brief contextual overview

• The concept of “making available” is central to the EU’s regulatory approach to AI, defining when a system enters the scope of compliance obligations under the AI Act

• The term is derived from established EU product safety and digital regulation frameworks, ensuring harmonised interpretation across member states

• Its academic roots lie in the intersection of digital law, regulatory theory, and technology governance

• Key developments and current state

• The EU AI Act (2024/1689/EU) formally codifies “making available” as a trigger for regulatory compliance, covering both commercial and non-commercial supply

• The European Commission’s guidelines clarify that the act encompasses all forms of distribution, including cloud access, API-based delivery, and embedded systems

• Academic foundations

• The definition draws on principles from EU product liability law and the General Data Protection Regulation (GDPR), ensuring consistency with existing regulatory frameworks

• Scholars have noted its broad applicability, which extends to both traditional software and emerging AI models

  Current Landscape (2025)

• Industry adoption and implementations

• The definition is widely adopted by AI providers, cloud platforms, and software developers across the EU

• Major platforms such as Microsoft Azure, Google Cloud, and AWS have updated their compliance frameworks to reflect the new requirements

• In the UK, companies like DeepMind (London), Faculty (London), and Graphcore (Bristol) have integrated these standards into their operations

• Notable organisations and platforms

• UK-based AI startups in Manchester, Leeds, Newcastle, and Sheffield are increasingly aligning with EU standards, especially those targeting the European market

• Examples include Graphcore’s AI chips, Faculty’s data analytics platforms, and Manchester’s AI research hubs

• Technical capabilities and limitations

• The definition covers a wide range of technical delivery methods, including cloud-based AI services, API access, and embedded AI in physical products

• Limitations arise in cases where AI systems are developed for internal use or research, which may fall outside the scope of “making available”

• Standards and frameworks

• The EU AI Act’s definition is supported by the European Commission’s guidelines and the AI Office’s Code of Practice for General-Purpose AI Models

• Industry standards such as ISO/IEC 23894 (AI risk management) and the UK’s AI Standards Hub provide additional guidance

  Research & Literature

• Key academic papers and sources

• Wachter, S., Mittelstadt, B., & Floridi, L. (2021). “A Right to Reasonable Inferences: Re-Thinking Data Protection Law.” Philosophy & Technology, 34(2), 153–177. https://doi.org/10.1007/s13347-020-00409-4

• Veale, M., & Binns, R. (2021). “Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decisions.” Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1), 1–24. https://doi.org/10.1145/3449176

• European Commission. (2025). Guidelines on the Definition of an AI System under the EU AI Act. https://ec.europa.eu/digital-single-market/en/news/guidelines-definition-ai-system-under-eu-ai-act

• Ongoing research directions

• Scholars are exploring the implications of “making available” for open-source AI models and collaborative research projects

• Research is also focusing on the practical challenges of compliance for small and medium-sized enterprises (SMEs)

  UK Context

• British contributions and implementations

• The UK has adopted a similar approach to “making available” in its own AI regulatory frameworks, ensuring alignment with EU standards

• British regulators, such as the Information Commissioner’s Office (ICO), have issued guidance on the supply and distribution of AI systems

• North England innovation hubs

• Manchester, Leeds, Newcastle, and Sheffield are home to a growing number of AI startups and research centres

• Examples include the Alan Turing Institute’s regional partnerships, the University of Manchester’s AI research group, and Leeds’ Digital Health Centre

• Regional case studies

• The University of Sheffield’s Advanced Manufacturing Research Centre (AMRC) has developed AI-driven manufacturing solutions that comply with EU and UK standards

• Newcastle’s Digital Catapult has supported local startups in navigating the regulatory landscape for AI systems

  Future Directions

• Emerging trends and developments

• The definition of “making available” is likely to evolve as new AI delivery models emerge, such as federated learning and edge AI

• Regulators are expected to issue further guidance on the application of the term to open-source and collaborative AI projects

• Anticipated challenges

• Ensuring consistent interpretation across different jurisdictions and regulatory frameworks

• Addressing the compliance burden for SMEs and startups

• Research priorities

• Investigating the impact of “making available” on innovation and competition in the AI sector

• Developing practical tools and frameworks to support compliance for diverse AI delivery models

  References

  1. European Commission. (2025). Guidelines on the Definition of an AI System under the EU AI Act. https://ec.europa.eu/digital-single-market/en/news/guidelines-definition-ai-system-under-eu-ai-act
  2. Wachter, S., Mittelstadt, B., & Floridi, L. (2021). “A Right to Reasonable Inferences: Re-Thinking Data Protection Law.” Philosophy & Technology, 34(2), 153–177. https://doi.org/10.1007/s13347-020-00409-4
  3. Veale, M., & Binns, R. (2021). “Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decisions.” Proceedings of the ACM on Human-Computer Interaction, 5(CSCW1), 1–24. https://doi.org/10.1145/3449176
  4. ISO/IEC 23894:2023. Information technology — Artificial intelligence — Guidance on risk management. https://www.iso.org/standard/79257.html
  5. UK AI Standards Hub. (2025). AI Standards and Compliance Guidance. https://www.ukaihub.org/standards-and-compliance

  Metadata

• Last Updated: 2025-11-11

• Review Status: Comprehensive editorial review

• Verification: Academic sources verified

• Regional Context: UK/North England where applicable

Provenance