{"id":88727,"date":"2026-07-05T08:00:00","date_gmt":"2026-07-05T06:00:00","guid":{"rendered":"https:\/\/www.mitsm.de\/wissen\/wie-haelt-man-interne-ki-richtlinien-rechtssicher-ein\/"},"modified":"2026-08-21T10:57:24","modified_gmt":"2026-08-21T08:57:24","slug":"wie-haelt-man-interne-ki-richtlinien-rechtssicher-ein","status":"publish","type":"knowledge","link":"https:\/\/www.mitsm.de\/wissen\/wie-haelt-man-interne-ki-richtlinien-rechtssicher-ein\/","title":{"rendered":"Wie h\u00e4lt man interne KI-Richtlinien rechtssicher ein?"},"content":{"rendered":"<p>Internal AI policies are legally sound when they fully cover the requirements of the EU AI Act, the GDPR, and where applicable ISO 42001, clearly define responsibilities, and are actively lived within the organisation. Anyone who merely creates a document without backing it up with processes, training, and documentation risks fines and liability exposure. This article answers the most important questions about legally compliant AI governance in organisations.<\/p>\n<h2>What legal requirements apply to internal AI policies?<\/h2>\n<p>Internal AI policies must at minimum address the requirements of the EU AI Act, the General Data Protection Regulation (GDPR), and employment law. For organisations operating high-risk AI systems, additional operator obligations apply. The legal framework is therefore multi-layered and requires a coordinated view of various regulatory instruments.<\/p>\n<p>The EU AI Act applies directly and classifies AI systems according to a risk-based approach. Operators of high-risk AI systems face particularly far-reaching obligations: they must ensure operation in accordance with the instructions for use, implement human oversight mechanisms, report serious incidents, and retain automated logs for six months. Those who use AI systems for emotion recognition or biometric categorisation must additionally fulfil information obligations towards affected individuals.<\/p>\n<p>In parallel, the GDPR requires a clear purpose limitation for AI-supported data processing activities, and in many cases a Data Protection Impact Assessment under Art. 35. Employment law complements this framework: where AI is used in the workplace, co-determination rights of the works council apply \u2014 for example when introducing technical monitoring systems or automations that affect jobs. The BSIG, with its requirements for risk management and information security, is also relevant as soon as a company is classified as a critical facility.<\/p>\n<p>Anyone wishing to orient themselves around a recognised management system standard will find a structured framework in the <a href=\"https:\/\/www.mitsm.de\/beratung\/iso-42001-audit\/\">ISO 42001 certification<\/a> that systematically addresses many of these legal requirements.<\/p>\n<h2>What must a legally sound AI policy contain as a minimum?<\/h2>\n<p>A legally sound AI policy must clearly define its scope, name roles and responsibilities, establish rules of conduct for AI use, and describe procedures for reporting problems. If any of these building blocks is missing, gaps arise that can lead to liability risks in serious cases.<\/p>\n<p>In detail, an AI policy should include the following core elements:<\/p>\n<ul>\n<li><strong>Scope:<\/strong> Which AI systems and use cases are covered? Does the policy apply to all employees or only specific departments?<\/li>\n<li><strong>Roles and responsibilities:<\/strong> Who is responsible for operating, monitoring, and approving AI systems? ISO 42001 explicitly requires that AI roles and responsibilities are defined and assigned in accordance with the needs of the organisation.<\/li>\n<li><strong>Usage rules:<\/strong> What is permitted, what is prohibited? This includes specifications on data input, handling of personal data, and labelling of AI-generated content.<\/li>\n<li><strong>Reporting procedures:<\/strong> A clear procedure for reporting concerns or incidents is mandatory. Operators of high-risk AI systems are also legally obliged to report serious incidents to providers and authorities.<\/li>\n<li><strong>Transparency obligations:<\/strong> In the case of automated decisions, affected individuals must be informed and have the right to an explanation of the decision-making process in individual cases.<\/li>\n<li><strong>Data protection requirements:<\/strong> Reference to internal GDPR processes and the obligation to conduct a Data Protection Impact Assessment for high-risk AI applications.<\/li>\n<\/ul>\n<h2>How are AI policies effectively implemented within an organisation?<\/h2>\n<p>An AI policy only becomes effective when it is embedded in everyday practice through concrete measures: training for employees, clear communication of the rules, and a corporate culture that actively promotes responsible AI use. A document alone is not enough.<\/p>\n<p>For practical implementation, a multi-stage approach is recommended. First, a skills gap analysis is needed to understand where knowledge gaps exist. Building on this, a learning concept should be established that combines basic training for all employees with role-specific deepening for those responsible for AI. Fears and resistance towards AI must be taken seriously and actively addressed.<\/p>\n<p>At the same time, organisations should promote so-called AI champions: employees who act as internal multipliers, answer questions, and moderate collegial exchange. Regular, transparent communication about the rationale, rules, and positive examples builds trust. Where a works council exists, its early involvement is not only legally required but also strategically sensible in order to secure acceptance.<\/p>\n<p>For organisations wishing to prepare their workforce for AI compliance in a structured way, mITSM offers practice-oriented <a href=\"https:\/\/www.mitsm.de\/schulung\/ki-kompetenz\/\">training courses on AI governance and compliance<\/a> that address precisely these implementation challenges.<\/p>\n<h2>How can compliance with AI policies be documented in a verifiable way?<\/h2>\n<p>Compliance with AI policies is made verifiable through systematic documentation: log files of automated systems, records of training sessions conducted, evidence of Data Protection Impact Assessments, and recorded review processes together form a robust compliance foundation.<\/p>\n<p>The EU AI Act prescribes a six-month retention obligation for automated logs for operators of high-risk AI systems. In addition, a functioning AI management system under ISO 42001 requires that resources, risks, and measures are fully recorded and documented in a traceable manner. For organisations pursuing ISO 42001 certification, complete documentation is not an option but a prerequisite.<\/p>\n<p>In practice, a centralised documentation structure with the following components has proven effective:<\/p>\n<ol>\n<li>Current register of all AI systems in use, with risk classification<\/li>\n<li>Evidence of Data Protection Impact Assessments conducted<\/li>\n<li>Records of human oversight and approval decisions<\/li>\n<li>Training records for all relevant employees<\/li>\n<li>Documented reports of incidents or concerns<\/li>\n<li>Records of policy reviews and changes made<\/li>\n<\/ol>\n<h2>What happens in the event of violations of internal AI policies?<\/h2>\n<p>Violations of internal AI policies can result in both employment law consequences for employees and regulatory consequences for the organisation. Violations of the EU AI Act can lead to significant fines, which can be substantial depending on the severity of the violation and the size of the organisation.<\/p>\n<p>At the regulatory level, the EU AI Act provides for a graduated system of sanctions. Serious violations \u2014 such as the use of prohibited AI practices or failure to fulfil reporting obligations for high-risk systems \u2014 can lead to fines of up to 35 million euros or seven percent of global annual turnover. In addition, there may be liability claims from affected individuals in the event of data protection violations in connection with AI applications.<\/p>\n<p>Internally, organisations should define clear escalation processes: Who is informed in the event of a violation? What immediate measures are to be initiated? How is the incident documented and evaluated? A functioning reporting procedure, as required by ISO 42001 under the point &#8222;reporting of concerns&#8220;, is not only a compliance requirement but also an effective instrument for the early detection of problems.<\/p>\n<h2>How often should AI policies be reviewed and updated?<\/h2>\n<p>AI policies should be reviewed at least once a year and on an ad hoc basis \u2014 for example, in the event of significant changes to the AI systems in use, new legal requirements, or following security-relevant incidents. ISO 42001 explicitly requires that the AI policy be reviewed at planned intervals and additionally as needed, in order to ensure its continued suitability, adequacy, and effectiveness.<\/p>\n<p>In practice, this means: a fixed review cycle should be anchored in the annual calendar. This process includes checking whether existing rules still align with the current legal framework, whether new AI applications within the organisation fall within the scope of the policy, and whether the defined measures are actually effective in practice.<\/p>\n<p>Ad hoc reviews are always required when new regulatory guidelines are published, when the organisation introduces new AI systems, or when incidents show that existing rules are insufficient. Given the ongoing implementation of the EU AI Act and the publication of supplementary guidelines by the European Commission and national authorities, further clarifications are expected in 2026 that may necessitate adjustments to internal policies.<\/p>\n<h2>How mITSM supports organisations with AI compliance<\/h2>\n<p>We at mITSM support specialists, managers, and organisations in building AI governance in a structured way and making it legally sound. Our training portfolio covers all relevant levels of AI compliance:<\/p>\n<ul>\n<li><strong>AI Manager training:<\/strong> Comprehensive further education on the EU AI Act, GDPR in the AI context, risk management, and internal AI governance<\/li>\n<li><strong>AI Compliance Officer:<\/strong> Specialised training for those responsible for managing and monitoring AI policies within the organisation<\/li>\n<li><strong>ISO 42001 Auditor:<\/strong> Preparation for auditing AI management systems in accordance with ISO 42001<\/li>\n<li><strong>In-house training:<\/strong> Standardised course formats delivered directly on-site with the client, bringing entire teams to the same level of knowledge<\/li>\n<li><strong>Certifications via ICO-Cert:<\/strong> Recognised personal certifications that concretely increase market value in the job market<\/li>\n<\/ul>\n<p>Our trainers are certified experts who bring practical knowledge and communicate complex compliance requirements in an understandable way. Whether as in-person training, online live sessions, or e-learning: we offer the right format for every need. Find out now about our <a href=\"https:\/\/www.mitsm.de\/schulung\/ki-kompetenz\/\">training offering on AI compliance and governance<\/a> and make your AI policies truly legally sound.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Bu\u00dfgelder bis 35 Mio. \u20ac: So machen Sie interne KI-Richtlinien wirklich rechtssicher \u2013 praxisnah erkl\u00e4rt.<\/p>\n","protected":false},"featured_media":84907,"parent":0,"menu_order":0,"template":"","tags":[],"knowledge_taxonomy":[3926],"class_list":["post-88727","knowledge","type-knowledge","status-publish","has-post-thumbnail","hentry","knowledge_taxonomy-wissenssammlung-kuenstliche-intelligenz"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Wie h\u00e4lt man interne KI-Richtlinien rechtssicher ein? - mITSM<\/title>\n<meta name=\"description\" content=\"KI-Richtlinien rechtssicher gestalten: EU AI Act, DSGVO &amp; ISO 42001 konform umsetzen \u2013 mit klaren Rollen, Schulungen und Dokumentation. 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