--- title: "C(2026) 4839 — Opinion — Assessment of the Code of Practice on AI-generated content [final]" shortTitle: "C(2026) 4839 — Opinion — Assessment of the Code of Practice on AI-generated content [final]" type: opinion instrument_type: opinion authority: Commission binding: false binding_character: non_binding legal_status: in_force regulation: AI Act aiact_level3: true mica_level2: false reference: "C(2026) 4839 final" legal_basis: "Articles 50(7) and 56(6) AI Act" date: 8 July 2026 source_link: "https://digital-strategy.ec.europa.eu/en/library/commission-opinion-assessment-code-practice-transparency-ai-generated-content" source_pdf: "https://ec.europa.eu/newsroom/dae/redirection/document/130913" lifecycle: "final" text_version: "Commission publication" source_url: "https://digital-strategy.ec.europa.eu/en/library/commission-opinion-assessment-code-practice-transparency-ai-generated-content" check_status: matched verified: true last_checked: 2026-10-26 checked_against: "the Commission publication" source: prepared_by: "European Commission" published_by: "European Commission" evidence: prepared_by: "C(2026) 4839 final" locator: "PDF page 1 (https://ec.europa.eu/newsroom/dae/redirection/document/130913)" document_type: "opinion" legal_nature: "not_legislation" addressees: "not stated in the document" dates: document_date: "2026-07-08" locators: document_date: "PDF page 1: \"8.7.2026\"" lifecycle_label: "final" --- **Opinion of the European Commission · not legislation · dated 8 Jul 2026 [final]** *Final · Commission publication · Checked against the Commission publication on 26 Oct 2026 · [Official source](https://digital-strategy.ec.europa.eu/en/library/commission-opinion-assessment-code-practice-transparency-ai-generated-content)* | | | |---|---| | **Full title** | C(2026) 4839 — Opinion — Assessment of the Code of Practice on AI-generated content \[final\] | | **Prepared by** | European Commission | | **Published by** | European Commission | | **Reference** | C(2026) 4839 final | | **Document type** | Opinion | | **Legal nature** | Not legislation | | **Addressees** | Not stated in the document | | **Dates** | Dated 8 July 2026 | | **Legal basis** | Articles 50(7) and 56(6) AI Act | | **Related instruments** | None recorded | | **Text on this page** | Word for word — the full text of the Commission publication | EUROPEAN COMMISSION Brussels, 8.7.2026 C(2026) 4839 final ## COMMISSION OPINION ## of 8.7.2026 on the assessment of the Code of Practice on Transparency of AI-generated content in accordance with Articles 50(7) and 56(6) of Regulation (EU) 2024/1689 ## COMMISSION OPINION of 8.7.2026 on the assessment of the Code of Practice on Transparency of AI-generated content in accordance with Articles 50(7) and 56(6) of Regulation (EU) 2024/1689 ## 1. LEGAL BASIS (1) On 10 June 2026, the Code of Practice on Transparency of AI-generated content (the “Code”) was published. It was drawn up pursuant to Article 50(7) of Regulation (EU) 2024/1689 of the European Parliament and of the Council on a European approach for Artificial Intelligence (the Artificial Intelligence Act or “AI Act”). The purpose of the Code is to facilitate the effective implementation of the obligations regarding the marking and labelling of artificially generated or manipulated content as provided in Articles 50(2) and (4) AI Act. The Code also facilitates the effective implementation of the horizontal requirements for disclosure envisaged in Article 50(5) AI Act. (2) Article 50(2) AI Act requires providers of AI systems (including general-purpose AI systems), that generate synthetic audio, image, video or text content, to ensure that the outputs of their AI system are marked in a machine-readable format and detectable as artificially generated or manipulated, unless limited exceptions apply. The technical solutions for marking and detection employed by providers must also meet four requirements for effectiveness, reliability, robustness and interoperability. (3) Article 50(4), subparagraph 1, AI Act requires deployers of an AI system that generates or manipulates image, audio or video content constituting a deep fake to disclose that the content has been artificially generated or manipulated. Subparagraph 2 of that provision requires deployers of an AI system that generates or manipulates text which is published with the purpose of informing the public on matters of public interest to disclose that the text has been artificially generated or manipulated, unless limited exceptions apply. (4) Article 50(5) requires the information referred to in paragraphs 1 to 4 of that provision to be provided to the natural persons concerned in a clear and distinguishable manner at the latest at the time of the first interaction or exposure. The information must conform to the applicable accessibility requirements. (5) Pursuant to Article 50(7) AI Act, the Commission may adopt an implementing act to approve codes of practice on the detection and marking of AI-generated and manipulated content in accordance with the procedure laid down in Article 56(6) AI Act. The Commission may also adopt common rules for the implementation of those obligations, if it deems that the code is not adequate. A contrario, it follows that the Commission has a corresponding obligation to assess the adequacy of the Code in accordance with the procedure referred to in Article 56(6) AI Act before proposing an implementing act to approve the Code, similar to the procedure foreseen for assessing the adequacy of Code of Practice on General-Purpose AI. In addition to a Commission adequacy assessment, Article 56(6) AI Act also refers to an adequacy assessment by the AI Board, which is composed of representatives from the Member States and their market surveillance authorities (“the Board”). The co-legislators approved the Commission’s Proposal for a Regulation of the European Parliament and of the Council amending Regulations (EU) 2024/1689 and (EU) 2018/1139 as regards the simplification of the implementation of harmonised rules on artificial intelligence, which will introduce changes to the procedure for the assessment of the adequacy of Codes of Practice under Article 50(7) AI Act. Once it enters into application, Article 56(6) AI Act will require the Commission to assess the adequacy of the Code after consultation of the Board. This assessment is undertaken by the Commission and the Board in parallel under the existing rules and will remain also valid after the entry into application of the AI Omnibus as long as the conclusions from both assessments are consistent. (6) This Opinion sets out the assessment by the Commission. The Board’s opinion on the adequacy of the Code will be published separately. (7) This Opinion does not prejudge any future action that the Commission, the Board, and other competent authorities, as applicable, may undertake in the enforcement of the AI Act. This document does not prevent the Commission from assessing the Code as inadequate in the future following its regular monitoring and evaluation of the achievement of the Code’s objectives and its contribution to the effective implementation of the AI Act pursuant to Articles 50(7) and Article 56(6) AI Act. ## 2. BACKGROUND (8) Codes of practice play an important role in the implementation of the AI Act. While they remain voluntary, the Union legislature considers such codes as an effective means to facilitate compliance by providers and deployers of AI systems and AI models with their obligations laid down in the AI Act. The Code sets out commitments and measures to which providers of generative AI systems, including general-purpose AI systems, and deployers of AI systems generating deepfakes and certain text may adhere to demonstrate their compliance with the obligations laid down in Articles 50(2) and 50(4) AI Act respectively and the horizontal disclosure requirements in Article 50(5) AI Act. (9) The Code was prepared following an iterative drafting process.(1) On 5 November 2025, that process was commenced with the ‘Kick-off Event for the Code Plenary’ involving more than 180 participants representing eligible respondents to the call to participate in the drawing-up of the Code, launched by the AI Office in early September 2025. A variety of interested stakeholders were involved in the drafting process, including providers of generative AI systems, developers of marking and detection techniques, associations of deployers of generative AI systems, civil society organisations, academic experts, standardisation organisations and specialised organisation with expertise in transparency, and providers of very large online platforms and of very large online search engines designated in accordance with Article 33(4) of Regulation (EU) 2022/2065. A list of those stakeholders and minutes of all meetings and workshops organised for the preparation of the Code are published on the Commission website. (1) See more details on Code of Practice on marking and labelling of AI-generated content \| Shaping Europe’s digital future The close involvement of Member States representatives as observers, as well as through the Board and its dedicated subgroup on transparency, was ensured throughout the process. The AI Office also invited other public bodies and agencies from all over the world working on transparency of AI-generated content to participate in the Code process as observers. (10) The Code’s drafting process involved two working groups chaired by independent, academic chairs and vice-chairs with renowned expertise in the respective areas. Working Group 1 led Section 1 of the Code on Rules for the marking and detection of artificially generated and manipulated content applicable to providers of generative AI systems (Articles 50(2) and (5) AI Act). Working Group 2 led Section 2 of the Code on Rules for labelling deep fakes and artificially generated and manipulated published text applicable to deployers of AI systems (Articles 50(4) and (5) AI Act). (11) The Code sets out eight commitments, divided into two categories. Section 1 of the Code operationalises the obligations in Articles 50(2) and (5) AI Act with four commitments on marking and ensuring detectability of AI-generated or manipulated content applicable to providers of AI systems generating or manipulating synthetic audio, image, text or video content. Section 2 of the Code operationalises the obligations in Articles 50(4) and (5) AI Act with four commitments on labelling deepfakes and AI-generated or manipulated text published with the purpose of informing the public on matters of public interest (referred to as ‘published text’) applicable to deployers of AI systems. (12) Under Section 1, Commitment 1 sets out the marking of AI-generated or manipulated content with a set of measures. Commitment 2 sets out measures for the detection of markings of AI-generated or manipulated content. Commitment 3 describes the measures to meet the requirements for marking and detection solutions. Commitment 4 addresses testing, verification and compliance. (13) Under Section 2, Commitment 1 sets out three measures to facilitate the disclosure of deep fakes and published text. Commitment 2 foresees three measures concerning internal processes for i) compliance, ii) awareness raising and literacy, and iii) review, feedback and cooperation with competent authorities. Commitment 3 sets out measures to operationalise the special regime for disclosure of deep fakes that are part of artistic, creative and similar works or programmes. Commitment 4 provides measures to ensure human review, editorial control and editorial responsibility for text published with the purpose to inform the public on matters of public interest applicable to deployers who wish to rely on the exception from the labelling obligation in Article 50(4) AI Act. ## 3. ASSESSMENT ### 3.1. Assessment criteria (14) The Commission must assess the adequacy of the Code pursuant to Article 50(7) AI Act. The purpose of the Code is to facilitate the effective implementation of the obligations regarding the detection and labelling of artificially generated or manipulated content laid down in Articles 50(2), (4) and (5) AI Act. The assessment is therefore whether the commitments set out in the Code ensure the “effective implementation” of those obligations. (15) Recital 135 AI Act specifies, in this respect, that the Code should support practical arrangements for making, as appropriate, the detection mechanisms accessible and facilitating cooperation with other actors along the value chain, disseminating content, or checking its authenticity and provenance to enable the public to effectively distinguish AI-generated content. (16) The facilitation of an effective implementation of Articles 50(2), (4) and (5) AI Act is assessed in the following sections 3.2 to 3.6 of this Opinion. ### 3.2. Contribution to the effective implementation of Article 50(2) and (5) of the AI Act (17) Section 1 of the Code aims to contribute to the effective implementation of the obligations imposed on providers of generative AI systems under Articles 50(2) and (5) AI Act. (18) Article 50(2) AI Act sets out a transparency obligation for providers of generative AI systems comprising three distinct, but inherently, interlinked elements. According to that provision, providers of generative AI systems must ensure: * that the outputs of the AI system are marked in a machine-readable format. * that the outputs are detectable as artificially generated or manipulated. * that the combination of the technical solutions for marking and detection meet the requirements of effectiveness, interoperability, robustness and reliability, insofar as this is technically feasible, taking into account the specificities and limitations of various types of content, the costs of implementation and the generally acknowledged state of the art, as may be reflected in relevant technical standards. (19) Article 50(5) AI Act further specifies that the information referred to under Article 50(2) AI Act – notably the result of the detection – should be provided to the natural persons exposed to the content in a clear and distinguishable manner at the latest at the time of the first interaction or exposure. (20) The Commitments and measures set out in Section 1 of the Code cover each of the aforementioned elements of the obligation laid down in Articles 50(2) and (5) AI Act and facilitate their effective implementation by providers of generative AI systems as follows. (21) Commitment 1 facilitates the effective implementation of the marking element of the transparency obligation with commitments from Signatories to implement a marking solution with regard to the audio, image, video or text content, or any combination thereof, generated or manipulated by the AI system which is placed on the market or put into service in the Union. Measure 1.1 specifies the machine-readable marking techniques that providers of generative AI systems may rely on to comply with that obligation, including a multi-layered approach of at least two layers (metadata and watermarks) for increased robustness aligned with the state of the art and relevant standards, while allowing flexibility for a single layer approach if an equivalent level of compliance can be demonstrated by the provider of the generative AI system. Measure 1.2 outlines the commitments for markings not to be removed. This measure * aims to advance the objective of effective marking, including through cooperation with other stakeholders in the value chain to preserve the marks. (22) Commitment 2 facilitates the effective implementation of the detectability element of the transparency obligation with commitments from Signatories to ensure that there are means to enable the detection of the machine-readable markings present in audio, image, video or text content, or a combination thereof, as generated or manipulated by their AI system. Measure 2.1 clarifies the requirements for the detection solution with regard to their availability, accessibility, personal data and security protection, and withdrawal. This is supported by recital 135 AI Act, which clarifies that the Code’s purpose is to support practical arrangements for making, as appropriate, the detection mechanisms accessible and to enable the public to effectively distinguish AI-generated content from other content. (23) Commitment 2 also facilitates the disclosure element of the transparency obligation with commitments from Signatories to ensure that the detection results are provided to natural persons that may be exposed to the content in a clear, distinguishable and accessible manner. Measure 2.3 further specifies this commitment with regards to the specific measures to implement clear and accessible disclosure of detection results to all natural persons in accordance with Article 50(5) AI Act. (24) Commitment 3 facilitates the effective implementation of the requirements for marking and detection solutions specified in Article 50(2) AI Act. Measure 3.1 details how to implement and assess in practice marking and detection solutions that are effective. Measure 3.2. details how to implement and assess in practice marking and detection solutions that are reliable. Measure 3.3 details how to implement and assess in practice marking and detection solutions that are robust. Measure 3.4 sets out a staged approach to the implementation of the watermarking and detection solutions that are interoperable. The latter measure includes clear commitments for the use of available open metadata standards, starting from the entry into application of the rules, and a minimum level of interoperability solutions for the watermarking detection mechanism to be implemented by 2 February 2027 to reduce the burden on providers of AI systems and enable a more seamless access for users. Such an approach constitutes a pragmatic step forward in a context where the state of the art does not yet support more mature and standardised solutions for watermarking and where the current ecosystem is fragmented and requires a certain level of protection to preserve the robustness of watermarking solutions. Furthermore, Signatories commit to cooperate towards advancing interoperability of watermarking and detection solutions and to implement improved and state of the art interoperability solutions and standards in a timely manner once they emerge. The Commission will monitor the implementation of this measure under the Code and reserves its right, in case of a lack of progress, to consider taking appropriate measures. (25) Commitment 4 facilitates the effective implementation of the transparency obligation under Articles 50(2) and (5) AI Act as a whole with commitments from Signatories to set up, keep up to date, and implement compliance, testing, verification, and monitoring processes to ensure the effective implementation of and to demonstrate compliance with the obligations set out in that provision and the commitments and the measures envisaged in Section 1 of the Code. Measure 4.1 specifies that Signatories will document, implement, and keep up to date, in line with the state of the art, a compliance process that describes, at a high-level, how they have implemented the different measures of Section 1 of the Code. Measure 4.2 clarifies ways for testing, verification, and monitoring to ensure continuous compliance of the marking and detection solutions before and after the AI systems are placed on the market or put into service in the Union. Measure 4.3 covers appropriate training for personnel with roles relevant to ensure compliance with Articles 50(2) and (5) and Article 4 AI Act. Measure 4.4 addresses cooperation with market surveillance authorities. The implementation of the measures may rely on existing processes and documentation and take into account the size and available resources of Signatories, which ensures proportionality and simplification, without necessarily affecting effectiveness. Commitment 4 is motivated by recital 135 AI Act, which clarifies that the Code’s purpose is to facilitate cooperation with other actors along the value chain. (26) Section 1 of the Code further contributes to the effective implementation of Article 50(2) AI Act by suggesting optional measures that are not required to ensure compliance with that provision and are therefore voluntary, but are nevertheless recommended. Those measures are conducive to achieving the goals of Article 50(2) AI Act, since the purpose of the Code, as clarified by recital 135 AI Act, is to enable natural persons to effectively distinguish AI-generated content. Measure 1.3 encourages providers of AI systems to provide provenance information and richer metadata that will help natural persons further obtain relevant information on the nature of the content and will increase trust in the information ecosystem. Measure 1.4 encourages providers to provide an optional functionality for a perceptible label that will also facilitate compliance for downstream deployers of AI systems subject to labelling obligations. Measure 2.2 opens the possibility for providers to include a forensic detection mechanism as part of their detection solution to address cases where metadata has been stripped and watermarks removed. Measure 2.4 supports literacy on AI marking and detection solutions that are essential for the broader effectiveness of the transparency obligations and the ability of natural persons to effectively distinguish AI-generated content from other content. Measure 3.5 encourages providers to invest in advancing the state of the art of marking and detection solutions to improve robustness and the effectiveness of those solutions. All these measures are also motivated by recital 135 AI Act, which clarifies that the Code’s purpose is to facilitate cooperation with other actors along the value chain, since these measures encourage cooperation with model providers, downstream deployers, end-users, civil society organisations, academia, independent researchers, providers of online platforms and search engines, market surveillance authorities, and other regulators. (27) Furthermore, Section 1 of the Code allows providers not covered by the transparency obligation laid down in Article 50(2) AI Act, such as providers of AI models and third-party providers of marking techniques and detection mechanisms that are provided independently from the AI system, to adhere to the Code as specified in the introduction to the Commitments. Those providers can also adhere on a voluntary basis and rely on the Code to demonstrate that their AI model or marking and detection solutions comply with Articles 50(2) and (5) AI Act, thus facilitating effective implementation and compliance for downstream providers of generative AI systems. The Code clarifies that references to Signatories throughout this Section of the Code shall be understood accordingly and that the commitments and the measures of Section 1 of the Code are applicable respectively to the Signatory’s generative AI model or marking and detection solutions. In doing so, the Code effectively achieves the objective set out in recital 135 AI Act, which is to facilitate cooperation with other actors along the value chain, and * facilitates the effective implementation of the transparency obligations laid down in Article 50(2) and (5) AI Act. (28) In light of the above, the Commission considers that Section 1 of the Code adequately facilitates the effective implementation of the transparency obligations laid down in Articles 50(2) and (5) AI Act and that providers of AI systems may rely on the Commitments and Measures set out therein to demonstrate compliance with those obligations. ### 3.3. Contribution to the effective implementation of Article 50(4) of the AI Act (29) Section 2 of the Code aims to contribute to the effective implementation of the transparency obligations applicable to deployers of generative AI systems laid down in Articles 50(4) and (5) of the AI Act. (30) Article 50(4) AI Act set out two transparency obligations for deployers of certain generative AI systems and their content: (31) First, deployers of AI systems that generate or manipulate image, audio or video content constituting a deep fake within the meaning of Article 3(60) AI Act must disclose that the content has been artificially generated or manipulated. Where the deep fake content forms part of an evidently artistic, creative, satirical, fictional or analogous work or programme, the transparency obligation is limited to disclosure of the existence of such generated or manipulated content in an appropriate manner that does not hamper the display or enjoyment of the work. (32) Second, deployers of AI systems that generate or manipulate text which is published with the purpose of informing the public on matters of public interest must disclose that the text has been artificially generated or manipulated. This obligation does not apply where the AI-generated or manipulated content has undergone a process of human review or editorial control, and where a natural or legal person holds editorial responsibility for the publication. (33) Article 50(5) AI Act further specifies that the information referred to under Article 50(4) AI Act (i.e. the applied measure that discloses that content has been artificially generated or manipulated) should be provided to the natural persons exposed to the content in a clear and distinguishable manner at the latest at the time of first exposure to the content. (34) The Commitments and measures set out in Section 2 of the Code cover each of the aforementioned elements of the obligation laid down in Articles 50(4) and (5) AI Act and facilitate their effective implementation by deployers of generative AI systems as follows. (35) Commitment 1 facilitates the consistent and effective disclosure of the artificial origin of deep fakes or published text on matters of public interest. It does so, in particular, by providing (i) three common EU icons (provided in Annex 1 of Section 2) that Signatories may use to ensure disclosure and (ii) common design specifications on which Signatories not using the common EU icon should rely, while allowing for certain degree of flexibility. These design specifications (Measure 1.1) are further complemented with placement specifications (Measure 1.2) that ensure clear and distinguishable placement of the icons or labels used by the Signatories, at the latest at the time of the exposure of the natural persons to the content, and that facilitate the effective implementation of Article 50(5) AI Act. Both sets of specifications rely on whether visual disclosure is possible. This ensures that the specifications are flexible and can be implemented across a range of use cases, sectors, and types of modalities, facilitating effective compliance by Signatories with Articles 50 (4) and (5) AI Act. (36) Commitment 2 facilitates the effective implementation of the disclosure obligations laid down in Article 50(4) AI Act by ensuring that Signatories put in place or maintain internal processes, awareness measures, and review mechanisms to that end. The implementation of the measures can rely on existing processes and documentation and take into account the size and available resources of Signatories. This ensures proportionality and simplification, without necessarily affecting effectiveness. Specifically, Measure 2.1 ensures that Signatories put in place or maintain appropriate internal compliance processes and documentation that specify how they implement the disclosure obligations. For Signatories that regularly use AI systems to create deep fakes or published text on matters of public interest, this is complemented with a commitment for a process to ensure and prevent potentially non-labelled or mislabelled content. Measures 2.2 (Awareness and literacy) and 2.3 (Review, feedback and cooperation with authorities) further ensure the effective implementation of Article 50(4) AI Act with commitments by Signatories to raise awareness and literacy among relevant personnel, to review observed or reported mislabelled content, and to cooperate with competent authorities. (37) Commitment 3 effectively enables deployers of generative AI systems to disclose deep fakes that form part of evidently artistic, creative, satirical, fictional or analogous work or programmes in a way that does not hamper the display or enjoyment of the work, including its normal exploitation and use, while maintaining the utility and quality of the work. In particular, it does so by allowing contextual disclosure where the information can be provided through the broader informative context, rather than as part of the content itself, while still mandating compliance with the design specifications of Measure 1.1 and the minimum requirements stemming from Article 50(5) AI Act. (38) Commitment 4 facilitates the effective implementation of the exception to the transparency obligation under Article 50(4), subparagraph 2, AI Act. By making a distinction between media service providers as defined in Article 2(2) of Regulation 2024/1083 and other actors with respect to the measures to be taken, a pertinent distinction is made that does not impact the effectiveness of the exception. On the contrary, this distinction and the related expected measures ensure that the exception can only be invoked by Signatories that have taken appropriate practical measures supporting effective human review or editorial control, while also identifying a natural or legal person assuming editorial responsibility. (39) Section 2 further contributes to the effective implementation of Article 50(4) AI Act by optional measures under the Code that are not legally required, but voluntary and nevertheless recommended. These measures are conducive to achieving the goal pursued by Article 50(4) AI Act to enable natural persons to effectively distinguish AI-generated or manipulated deep fakes and published text on matters of public interest. For example, Section 2 enables Signatories and the associations of which they are a part to jointly establish common good practices for their sector or industry, which can provide further details for the implementation of the Commitments and Measures specified in Section 2. Sub-measure 1.2.1 encourages Signatories to collaborate, on a best effort basis, with actors whose services or products they use to further distribute or disseminate the deep fake or published text to preserve the icon or equivalent label with the objective of ensuring that the required disclosure accompanies the deep fake or published text throughout its further distribution. This directly serves the objective of the Code of Practice, mentioned by Recital 135 AI Act to facilitate cooperation with other actors along the value chain disseminating content and to enable the public to effectively distinguish AI-generated content from other content. Moreover, Measure 1.3 encourages Signatories to support the work of a task-force that is tasked, inter alia, with further developing and promoting the uptake of the common EU icon and providing a forum among Signatories to exchange good practices. Measure 2.1 encourages Signatories to publish information on their disclosure solution in order to enhance public understanding of their practices. (40) In light of the above, the Commission considers that Section 2 of the Code adequately facilitates the effective implementation of the transparency obligations laid down Articles 50(4) and (5) AI Act and that deployers of AI systems may rely on the Commitments and Measures set out therein to demonstrate compliance with those obligations. ### 3.4. Additional consideration for the facilitation of an effective implementation: clear objectives, guiding recitals, commitments and measures (41) Each section of the Code outlines clear objectives and includes guiding principles that provide clarity to providers, deployers, and competent market surveillance authorities in the implementation of the commitments and the measures envisaged in the Code. (42) In addition, the Commitments entail purpose-clauses phrased as “in order to” or “for the purpose of” that set out the Commitments’ specific objectives (see, for example, Commitment 1 of each Section). (43) Moreover, measures distinguish between varying levels of legal commitment – using terms such as “will,” “encourages,” and “may” – to ensure clarity and eliminate ambiguity for future Signatories. These terms have been explicitly defined. (44) Section 1 enhances transparency by incorporating a glossary that defines key technical terms used in the Code. (45) Section 2 further supports practical understanding through an annex detailing the publicly available EU icon. (46) The Code’s Commitments and Measures outlined above are clearly directed to achieve their specific objectives described in their purpose-clauses and, in doing so, facilitating an effective implementation of the obligations under Articles 50(2) and Article 50(4) AI Act and the horizontal disclosure requirements in Article 50(5) AI Act. ### 3.5. Practical solutions accounting for the needs of interested parties (47) To facilitate the effective implementation of the transparency obligations, the development of the Code must account for the needs and interests of all stakeholders. This ensures that practical and workable solutions are identified, while enabling providers and deployers to sign up to the Code with ease. (48) Throughout the development process, stakeholder feedback has been actively sought and incorporated in an inclusive and transparent manner, ensuring that the final Code duly supports the practical implementation of the commitments undertaken by Signatories. ### 3.6. Code of Practice and Guidelines on Article 50 AI Act (49) Furthermore, the Code does not alter the Commission’s responsibility to provide guidance on the application of Article 50 AI Act. To provide clarity on the scope and legal concepts of the transparency obligations under Article 50 AI Act, the Commission will issue guidelines, as required under Article 96(1)(d) AI Act. Those guidelines will be relevant to understand concepts outlined in the Code and, in conjunction with the Code, will contribute to the effective implementation of Articles 50(2),(4) and (5) AI Act. ## 4. REVIEW AND ADAPTATION OF THE CODE (50) In accordance with Article 56(6) AI Act, the AI Office and the Board will regularly monitor and evaluate the achievement of the objectives of the Code and its contribution to the effective implementation of Articles 50(2),(4) and (5) AI Act, particularly in light of the rapidly evolving landscape of technologies, as well as risks of misinformation and manipulation at scale, fraud, impersonation and consumer deception, which both transparency obligations aim to address. (51) The AI Office will consider facilitating formal updates to the Code at least every two years, for instance based on the emergence of standards or relevant technological developments. To monitor the achievement of the objectives of the Code, the AI Office will remain in exchange with Signatories to understand where implementation support is necessary, and it may cooperate with national competent authorities, downstream providers, rightsholders, and other actors. It will also support the establishment and functioning of the task-forces envisaged under both sections of the Code, which will play a key role to advance the effective implementation of the Code and keep it practical, aligned with the state of the art, and future-proof. ## 5. CONCLUSION (52) In light of the foregoing, the Commission concludes that the Code of Practice on Transparency of AI-generated content adequately covers the obligations provided for in Articles 50(2), (4) and (5) AI Act and facilitates their effective implementation, thereby meeting the Code’s aims in accordance with Article 50(7) AI Act. Providers and deployers of AI systems falling within the scope of the transparency obligations laid down in Articles 50(2), (4) and (5) AI Act may rely on the Code as the EU-wide recognised instrument that is considered adequate to ensure compliance with their respective obligations, regardless of their place of establishment, operation or competent market surveillance authority, while recognising that adherence to the Code does not constitute conclusive evidence of compliance with these obligations. Done at Brussels, 8.7.2026 For the Commission Henna Virkkunen Executive Vice-President ## Related Level 1 articles - [Article 50 — Transparency obligations for providers and deployers of certain AI systems](../../articles/50.md) - [Article 56 — Codes of practice](../../articles/56.md)