[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fxmLUKnoXD-Qrg6OiS9uejgD_D84ZB4I9YMkjuNrv6FY":3,"$fDuOfbrGklFg9DNstLQj01v77JKgm8YTNP3W1V3nd5U4":112,"faq-section-":259,"white_papers":260},{"tableOfContents":4,"markDownContent":5,"htmlContent":6,"metaTitle":7,"metaDescription":8,"wordCount":9,"readTime":10,"title":11,"nbDownloads":12,"excerpt":13,"lang":14,"url":15,"intro":8,"featured":4,"state":16,"author":17,"authorId":18,"datePublication":23,"dateCreation":24,"dateUpdate":25,"mainCategory":26,"categories":42,"metaDatas":83,"imageUrl":102,"imageThumbUrls":103,"id":111},false,"With the AI Act's obligations coming into force in stages, many organisations have launched an \"AI compliance\" project. Some call it \"AI governance\". Others use the two terms interchangeably.\n\nIn practice, they don't mean the same thing. **AI compliance** is about meeting the legal obligations that apply to your AI systems.[ **AI governance**](https://www.dastra.eu/en/resources/glossary/ai-governance/59514) is the internal system that decides how your organisation uses AI, who is accountable, and which risks it is willing to take.\n\nMixing them up has consequences. An organisation can tick every box of an AI Act checklist and still have no real control over how AI is used across its teams. Another can have a well-designed governance framework and still miss a legal obligation that applies to one of its systems.\n\n## What is AI compliance?\n\nAI compliance means **meeting the legal and regulatory requirements that apply to AI systems**. In the EU, that mainly means the AI Act, but also the GDPR whenever personal data is involved, as well as sector rules (finance, health, employment).\n\nCompliance answers precise questions. For instance, if we're basing the reflexion on the EU AI Act, the type of questions would be:\n\n- **What is our role?** Provider, deployer, importer or distributor under the AI Act.\n- **What is the risk level of each system?** Prohibited, high-risk, subject to transparency obligations, or minimal risk.\n- **Which obligations follow?** For example, [AI literacy](https://www.dastra.eu/en/resources/glossary/ai-literacy/59507) (Article 4), transparency towards users (Article 50), or, for high-risk systems, a quality management system (Article 17) and human oversight.\n- **Can we prove it?** Documentation, logs, assessments, contracts.\n\nThe stakes are concrete. Under Article 99 of the AI Act, prohibited practices can lead to fines of up to €35 million or 7% of worldwide annual turnover. Breaches of most other obligations, including those for high-risk systems, can reach €15 million or 3%.\n\nCompliance is driven from the outside: the law sets the requirements, and the organisation demonstrates that it meets them. It is measurable, and it has deadlines.\n\n## What is AI governance?\n\nAI governance is **the set of roles, rules and processes an organisation puts in place to steer its use of AI**. It goes beyond what the law requires.\n\nGovernance answers different questions:\n\n- **What do we want to do with AI**, and what do we refuse to do?\n- **Who decides** whether a new tool can be deployed?\n- **Who owns the risk** once it is live?\n- **What is our risk appetite**, and does each use case fit within it?\n- **How do we stay in control** as tools, suppliers and uses change?\n\nGovernance is driven from the inside. No regulator imposes a single model, and the AI Act does not create a dedicated function equivalent to the DPO. Each organisation designs the structure that fits its size, sector and culture.\n\n## AI compliance vs AI governance: the key differences\n\n### \n\n|  | AI compliance | AI governance |\n| --- | --- | --- |\n| **Purpose** | Meet legal obligations | Steer and control the use of AI |\n| **Driven by** | Laws and regulators | The organisation’s strategy and values |\n| **Scope** | Systems covered by the regulation | All AI use, including what the law does not cover |\n| **Key question** | “Are we compliant?” | “Are we in control?” |\n| **Owned by** | Legal, compliance, DPO | Cross-functional: management, business owners, legal, security, data |\n| **Flexibility** | Low: requirements are set by law | High: adapted to size, sector and risk appetite |\n| **Typical outputs** | Classification, documentation, contracts, notices | Policies, roles, decision processes, risk acceptance |\n| **How it is measured** | Audits, documentation, conformity assessments | Coverage of the AI register, review cycles, tracked risk acceptance, training completed |\n| **Time frame** | Legal deadlines & ongoing | Ongoing |\n\n## Why the confusion is risky\n\n**Compliance without governance** has a one-shot approach. The register is filled in once, the assessments are done for the deadline, and six months later the inventory no longer reflects reality. New tools arrive through suppliers, AI features are switched on in existing software, and nobody is in charge of catching them.\n\n**Governance without compliance** produces a blind spot. Roles and committees exist, but nobody has checked whether a recruitment tool falls under the high-risk category, or whether the contract with the supplier covers the obligations that apply.\n\nThere is a third risk, less visible. The AI Act focuses on certain uses. A tool can be **minimal risk under the AI Act and still be critical to the business**, for example if it is embedded across several systems and a wrong output would be costly. Only governance will catch that.\n\n## How AI compliance and AI governance work together\n\nThe simplest way to see it: **governance is the structure, compliance is one of the things it delivers**.\n\nA solid AI governance framework makes compliance sustainable. In practice, it usually rests on four building blocks:\n\n1. **An AI register.** An inventory of AI systems and their use cases, kept up to date. It plays the same role for AI governance as the record of processing activities does for data protection.\n2. **A repeatable assessment.** Each new tool or supplier goes through the same steps: what the supplier claims, how the tool will really be used, and what risks follow.\n3. **Clear accountability.** The business owner owns the use case and its risk. Legal, data protection and security teams advise and propose measures. Risk acceptance is documented.\n4. **Ongoing review.** Systems, suppliers and regulations change. Governance defines when a use case must be reassessed.\n\nCompliance then becomes the output of a system that already works, rather than a separate project restarted at every deadline.\n\n## Where to start?\n\nMost organisations are still early. Some rely on recent regulatory delays to start working on this later on. However, the best way is to start building the proper foundations.\n\nA pragmatic starting point:\n\n- **Map what already exists**: AI tools in use (declared or not), existing policies, and what the business plans to do next.\n- **Qualify each system**: your role and its risk level under the AI Act.\n- **Assign owners**: one accountable person per use case.\n- **Build on your GDPR program**: AI systems that process personal data are already in your register, your DPIAs and your supplier reviews. There is no need to start from scratch.\n\n## **Build your AI governance and compliance in one place**\n\nDastra helps you build your AI register, qualify your systems under the AI Act, run supplier and use-case assessments, and link everything to your GDPR compliance.\n\n{% button href=\"https://www.dastra.eu/en/contacts/demo\" text=\"Book a demo\" target=\"\\_blank\" role=\"button\" class=\"btn btn-primary\" %}\n\n---","\u003Cp>With the AI Act's obligations coming into force in stages, many organisations have launched an \"AI compliance\" project. Some call it \"AI governance\". Others use the two terms interchangeably.\u003C/p>\n\u003Cp>In practice, they don't mean the same thing. \u003Cstrong>AI compliance\u003C/strong> is about meeting the legal obligations that apply to your AI systems.\u003Ca href=\"https://www.dastra.eu/en/resources/glossary/ai-governance/59514\"> \u003Cstrong>AI governance\u003C/strong>\u003C/a> is the internal system that decides how your organisation uses AI, who is accountable, and which risks it is willing to take.\u003C/p>\n\u003Cp>Mixing them up has consequences. An organisation can tick every box of an AI Act checklist and still have no real control over how AI is used across its teams. Another can have a well-designed governance framework and still miss a legal obligation that applies to one of its systems.\u003C/p>\n\u003Ch2 id=\"what-is-ai-compliance\">What is AI compliance?\u003C/h2>\n\u003Cp>AI compliance means \u003Cstrong>meeting the legal and regulatory requirements that apply to AI systems\u003C/strong>. In the EU, that mainly means the AI Act, but also the GDPR whenever personal data is involved, as well as sector rules (finance, health, employment).\u003C/p>\n\u003Cp>Compliance answers precise questions. For instance, if we're basing the reflexion on the EU AI Act, the type of questions would be:\u003C/p>\n\u003Cul>\n\u003Cli>\u003Cstrong>What is our role?\u003C/strong> Provider, deployer, importer or distributor under the AI Act.\u003C/li>\n\u003Cli>\u003Cstrong>What is the risk level of each system?\u003C/strong> Prohibited, high-risk, subject to transparency obligations, or minimal risk.\u003C/li>\n\u003Cli>\u003Cstrong>Which obligations follow?\u003C/strong> For example, \u003Ca href=\"https://www.dastra.eu/en/resources/glossary/ai-literacy/59507\">AI literacy\u003C/a> (Article 4), transparency towards users (Article 50), or, for high-risk systems, a quality management system (Article 17) and human oversight.\u003C/li>\n\u003Cli>\u003Cstrong>Can we prove it?\u003C/strong> Documentation, logs, assessments, contracts.\u003C/li>\n\u003C/ul>\n\u003Cp>The stakes are concrete. Under Article 99 of the AI Act, prohibited practices can lead to fines of up to €35 million or 7% of worldwide annual turnover. Breaches of most other obligations, including those for high-risk systems, can reach €15 million or 3%.\u003C/p>\n\u003Cp>Compliance is driven from the outside: the law sets the requirements, and the organisation demonstrates that it meets them. It is measurable, and it has deadlines.\u003C/p>\n\u003Ch2 id=\"what-is-ai-governance\">What is AI governance?\u003C/h2>\n\u003Cp>AI governance is \u003Cstrong>the set of roles, rules and processes an organisation puts in place to steer its use of AI\u003C/strong>. It goes beyond what the law requires.\u003C/p>\n\u003Cp>Governance answers different questions:\u003C/p>\n\u003Cul>\n\u003Cli>\u003Cstrong>What do we want to do with AI\u003C/strong>, and what do we refuse to do?\u003C/li>\n\u003Cli>\u003Cstrong>Who decides\u003C/strong> whether a new tool can be deployed?\u003C/li>\n\u003Cli>\u003Cstrong>Who owns the risk\u003C/strong> once it is live?\u003C/li>\n\u003Cli>\u003Cstrong>What is our risk appetite\u003C/strong>, and does each use case fit within it?\u003C/li>\n\u003Cli>\u003Cstrong>How do we stay in control\u003C/strong> as tools, suppliers and uses change?\u003C/li>\n\u003C/ul>\n\u003Cp>Governance is driven from the inside. No regulator imposes a single model, and the AI Act does not create a dedicated function equivalent to the DPO. Each organisation designs the structure that fits its size, sector and culture.\u003C/p>\n\u003Ch2 id=\"ai-compliance-vs-ai-governance-the-key-differences\">AI compliance vs AI governance: the key differences\u003C/h2>\n\u003Ch3 id=\"section\">\u003C/h3>\n\u003Ctable>\n\u003Cthead>\n\u003Ctr>\n\u003Cth>\u003C/th>\n\u003Cth>AI compliance\u003C/th>\n\u003Cth>AI governance\u003C/th>\n\u003C/tr>\n\u003C/thead>\n\u003Ctbody>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Purpose\u003C/strong>\u003C/td>\n\u003Ctd>Meet legal obligations\u003C/td>\n\u003Ctd>Steer and control the use of AI\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Driven by\u003C/strong>\u003C/td>\n\u003Ctd>Laws and regulators\u003C/td>\n\u003Ctd>The organisation’s strategy and values\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Scope\u003C/strong>\u003C/td>\n\u003Ctd>Systems covered by the regulation\u003C/td>\n\u003Ctd>All AI use, including what the law does not cover\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Key question\u003C/strong>\u003C/td>\n\u003Ctd>“Are we compliant?”\u003C/td>\n\u003Ctd>“Are we in control?”\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Owned by\u003C/strong>\u003C/td>\n\u003Ctd>Legal, compliance, DPO\u003C/td>\n\u003Ctd>Cross-functional: management, business owners, legal, security, data\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Flexibility\u003C/strong>\u003C/td>\n\u003Ctd>Low: requirements are set by law\u003C/td>\n\u003Ctd>High: adapted to size, sector and risk appetite\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Typical outputs\u003C/strong>\u003C/td>\n\u003Ctd>Classification, documentation, contracts, notices\u003C/td>\n\u003Ctd>Policies, roles, decision processes, risk acceptance\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>How it is measured\u003C/strong>\u003C/td>\n\u003Ctd>Audits, documentation, conformity assessments\u003C/td>\n\u003Ctd>Coverage of the AI register, review cycles, tracked risk acceptance, training completed\u003C/td>\n\u003C/tr>\n\u003Ctr>\n\u003Ctd>\u003Cstrong>Time frame\u003C/strong>\u003C/td>\n\u003Ctd>Legal deadlines & ongoing\u003C/td>\n\u003Ctd>Ongoing\u003C/td>\n\u003C/tr>\n\u003C/tbody>\n\u003C/table>\n\u003Ch2 id=\"why-the-confusion-is-risky\">Why the confusion is risky\u003C/h2>\n\u003Cp>\u003Cstrong>Compliance without governance\u003C/strong> has a one-shot approach. The register is filled in once, the assessments are done for the deadline, and six months later the inventory no longer reflects reality. New tools arrive through suppliers, AI features are switched on in existing software, and nobody is in charge of catching them.\u003C/p>\n\u003Cp>\u003Cstrong>Governance without compliance\u003C/strong> produces a blind spot. Roles and committees exist, but nobody has checked whether a recruitment tool falls under the high-risk category, or whether the contract with the supplier covers the obligations that apply.\u003C/p>\n\u003Cp>There is a third risk, less visible. The AI Act focuses on certain uses. A tool can be \u003Cstrong>minimal risk under the AI Act and still be critical to the business\u003C/strong>, for example if it is embedded across several systems and a wrong output would be costly. Only governance will catch that.\u003C/p>\n\u003Ch2 id=\"how-ai-compliance-and-ai-governance-work-together\">How AI compliance and AI governance work together\u003C/h2>\n\u003Cp>The simplest way to see it: \u003Cstrong>governance is the structure, compliance is one of the things it delivers\u003C/strong>.\u003C/p>\n\u003Cp>A solid AI governance framework makes compliance sustainable. In practice, it usually rests on four building blocks:\u003C/p>\n\u003Col>\n\u003Cli>\u003Cstrong>An AI register.\u003C/strong> An inventory of AI systems and their use cases, kept up to date. It plays the same role for AI governance as the record of processing activities does for data protection.\u003C/li>\n\u003Cli>\u003Cstrong>A repeatable assessment.\u003C/strong> Each new tool or supplier goes through the same steps: what the supplier claims, how the tool will really be used, and what risks follow.\u003C/li>\n\u003Cli>\u003Cstrong>Clear accountability.\u003C/strong> The business owner owns the use case and its risk. Legal, data protection and security teams advise and propose measures. Risk acceptance is documented.\u003C/li>\n\u003Cli>\u003Cstrong>Ongoing review.\u003C/strong> Systems, suppliers and regulations change. Governance defines when a use case must be reassessed.\u003C/li>\n\u003C/ol>\n\u003Cp>Compliance then becomes the output of a system that already works, rather than a separate project restarted at every deadline.\u003C/p>\n\u003Ch2 id=\"where-to-start\">Where to start?\u003C/h2>\n\u003Cp>Most organisations are still early. Some rely on recent regulatory delays to start working on this later on. However, the best way is to start building the proper foundations.\u003C/p>\n\u003Cp>A pragmatic starting point:\u003C/p>\n\u003Cul>\n\u003Cli>\u003Cstrong>Map what already exists\u003C/strong>: AI tools in use (declared or not), existing policies, and what the business plans to do next.\u003C/li>\n\u003Cli>\u003Cstrong>Qualify each system\u003C/strong>: your role and its risk level under the AI Act.\u003C/li>\n\u003Cli>\u003Cstrong>Assign owners\u003C/strong>: one accountable person per use case.\u003C/li>\n\u003Cli>\u003Cstrong>Build on your GDPR program\u003C/strong>: AI systems that process personal data are already in your register, your DPIAs and your supplier reviews. There is no need to start from scratch.\u003C/li>\n\u003C/ul>\n\u003Ch2 id=\"build-your-ai-governance-and-compliance-in-one-place\">\u003Cstrong>Build your AI governance and compliance in one place\u003C/strong>\u003C/h2>\n\u003Cp>Dastra helps you build your AI register, qualify your systems under the AI Act, run supplier and use-case assessments, and link everything to your GDPR compliance.\u003C/p>\n\u003Cdiv class=\"content-btn-container\">\u003Ca href=\"https://www.dastra.eu/en/contacts/demo\" target=\"_blank\" role=\"button\" class=\"btn btn-primary\">Book a demo\u003C/a>\u003C/div>\n\u003Chr />\n","AI compliance vs AI governance: what’s the difference?","AI compliance and AI governance are often confused. Learn how they differ, how they work together, and why you need both under the AI Act.",1097,6,"AI compliance vs AI governance: what's the difference, and why does it matter?",0,"","en","ai-compliance-vs-ai-governance","Published",{"id":18,"displayName":19,"avatarUrl":20,"bio":21,"blogUrl":21,"color":21,"userId":18,"creationDate":22},20352,"Leïla Sayssa","https://static.dastra.eu/tenant-3/avatar/20352/TDYeY3C8Rz1lLE/dpo-avatar-h01-150.png",null,"2025-03-03T11:08:22","2026-10-29T13:20:00","2026-10-29T13:20:29.6026686","2026-10-29T15:01:55.2480629",{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":32},2,"Blog","A list of curated articles provided by the community","blog","#28449a",[33,36,39],{"lang":34,"name":28,"description":35},"fr","Une liste d'articles rédigés par la communauté",{"lang":37,"name":28,"description":38},"es","Una lista de artículos escritos por la comunidad",{"lang":40,"name":28,"description":41},"de","Eine Liste von Artikeln, die von der Community verfasst wurden",[43,48,65],{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":44},[45,46,47],{"lang":34,"name":28,"description":35},{"lang":37,"name":28,"description":38},{"lang":40,"name":28,"description":41},{"id":49,"name":50,"description":51,"url":52,"color":53,"parentId":27,"count":21,"imageUrl":21,"parent":54,"order":27,"translations":59},220,"Compliance","Regulatory news, practical guides and analysis to keep your organization compliant with the GDPR and beyond.","compliance","#000000",{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":55},[56,57,58],{"lang":34,"name":28,"description":35},{"lang":37,"name":28,"description":38},{"lang":40,"name":28,"description":41},[60,63],{"lang":34,"name":61,"description":62},"Conformité","Actualités réglementaires, guides pratiques et analyses pour maintenir votre organisation en conformité RGPD et au-delà.",{"lang":40,"name":50,"description":64},"Regulatorische Neuigkeiten, Praxisleitfäden und Analysen, um Ihre Organisation DSGVO-konform und darüber hinaus aufzustellen.",{"id":66,"name":67,"description":68,"url":69,"color":53,"parentId":27,"count":21,"imageUrl":21,"parent":70,"order":75,"translations":76},221,"AI Governance","Best practices, regulatory frameworks and real-world insights to manage AI responsibly and in compliance with the AI Act.","ai-governance",{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":71},[72,73,74],{"lang":34,"name":28,"description":35},{"lang":37,"name":28,"description":38},{"lang":40,"name":28,"description":41},3,[77,80],{"lang":34,"name":78,"description":79},"Gouvernance de l'IA","Bonnes pratiques, cadres réglementaires et retours d'expérience pour piloter l'IA de façon responsable et conforme à l'AI Act.",{"lang":40,"name":81,"description":82},"KI-Governance","Best Practices, regulatorische Rahmenbedingungen und Praxiserfahrungen für einen verantwortungsvollen KI-Einsatz im Einklang mit dem AI Act.",[84],{"typeMetaDataId":85,"value":86,"id":101},9,{"title":87,"items":88},"FAQ: AI governance vs AI compliance ",[89,92,95,98],{"question":90,"answer":91},"Is AI governance mandatory under the AI Act?","\u003Cp>The AI Act does not require a specific governance structure. However, several obligations, such as AI literacy, human oversight and, for providers of high-risk systems, a quality management system, are very difficult to meet without one.\u003C/p>",{"question":93,"answer":94},"Who is responsible for AI compliance in an organisation?","\u003Cp>The AI Act assigns obligations to roles (provider, deployer), not to a job title. Inside the organisation, responsibility is often shared between legal, compliance, the DPO, the CISO and business owners. Governance is what makes that split explicit.\u003C/p>",{"question":96,"answer":97},"Is AI governance the same as data governance?","\u003Cp>No, but they overlap. Data governance covers the quality, use and protection of data. AI governance covers the systems that use that data, the decisions they influence and the risks they create.\u003C/p>",{"question":99,"answer":100},"Can ISO/IEC 42001 replace AI Act compliance?","\u003Cp>No. ISO/IEC 42001 is a management system standard that helps structure AI governance. It does not, on its own, give a presumption of conformity with the AI Act.\u003C/p>",118592,"https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-original.jpg",[104,105,106,107,108,109,110],"https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-1000.webp","https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16.webp","https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-1500.webp","https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-800.webp","https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-600.webp","https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-300.webp","https://static.dastra.eu/content/ce3d3fb4-d1e8-4afc-9e8a-381874614625/visuel-article-16-100.webp",60821,{"total":113,"items":114,"parent":254},8,[115,136,156,177,199,219,228,237],{"id":116,"name":117,"description":118,"url":119,"color":120,"parentId":27,"count":21,"imageUrl":21,"parent":121,"order":113,"translations":126},20,"Inside Dastra","Go behind the scenes at Dastra: company news, culture, events, team highlights, and the people driving our GDPR solution.","dastra-life","#e3cf68",{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":122},[123,124,125],{"lang":34,"name":28,"description":35},{"lang":37,"name":28,"description":38},{"lang":40,"name":28,"description":41},[127,130,133],{"lang":34,"name":128,"description":129},"Vie de Dastra","Plongez dans les coulisses de Dastra : actualités internes, culture d’entreprise, événements, équipes et engagements. Découvrez qui se cache derrière notre solution RGPD.",{"lang":40,"name":131,"description":132},"Innerhalb von Dastra","Eintauchen in das Unternehmen",{"lang":37,"name":134,"description":135},"Dentro de Dastra","Sumérjase en la empresa",{"id":137,"name":138,"description":139,"url":140,"color":53,"parentId":27,"count":21,"imageUrl":21,"parent":141,"order":146,"translations":147},69,"Expertise","Gain insights from our experts on GDPR compliance, data protection, and privacy challenges. In-depth articles, professional analysis, and real-world best practices.","indepth",{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":142},[143,144,145],{"lang":34,"name":28,"description":35},{"lang":37,"name":28,"description":38},{"lang":40,"name":28,"description":41},7,[148,150,153],{"lang":34,"name":138,"description":149},"Bénéficiez des conseils de nos experts sur la conformité RGPD, la protection des données et les enjeux privacy. Articles de fond, analyses et retours d’expérience métier.",{"lang":40,"name":151,"description":152},"Fachwissen","Entdecken Sie die Artikel unserer DSGVO-Experten",{"lang":37,"name":154,"description":155},"Experiencia","Descubre los artículos de nuestros expertos en Privacy",{"id":157,"name":158,"description":159,"url":160,"color":161,"parentId":27,"count":21,"imageUrl":21,"parent":162,"order":10,"translations":167},4,"Use cases","Discover how companies use Dastra to manage their GDPR compliance. Testimonials, use cases, and real-world integrations of our privacy management solution.","case-studies","#b61b9c",{"id":27,"name":28,"description":29,"url":30,"color":31,"parentId":21,"count":21,"imageUrl":21,"parent":21,"order":12,"translations":163},[164,165,166],{"lang":34,"name":28,"description":35},{"lang":37,"name":28,"description":38},{"lang":40,"name":28,"description":41},[168,171,174],{"lang":34,"name":169,"description":170},"Retours d'expérience","Découvrez comment les entreprises utilisent Dastra pour piloter leur conformité RGPD. 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