Building an AI governance structure in your company means defining clear responsibilities, policies, control mechanisms, and processes for the entire lifecycle of AI systems. This applies to both the technical and the organisational level. The following questions clarify the most important building blocks, responsibilities, and implementation steps in detail.<\/p>\n
An AI governance structure consists of four core areas: a documented AI policy, clearly assigned roles and responsibilities, a risk management process, and mechanisms for monitoring and continuous improvement. Together, these elements form the framework within which companies can deploy AI systems responsibly.<\/p>\n
In detail, a complete AI governance structure includes the following components:<\/p>\n
This framework is aligned with the international standard ISO 42001, which defines minimum requirements for an AI management system. The standard structures these requirements into chapters such as organisational context, leadership, planning, operation, and improvement.<\/p>\n
Companies need an AI governance structure because the uncontrolled use of AI systems creates legal, ethical, and economic risks that cannot be managed without regulated processes and responsibilities. With the EU AI Act, binding requirements will apply from 2026 onwards that cannot be met without a functioning governance structure.<\/p>\n
Beyond regulatory compliance, there are further reasons for structured AI governance:<\/p>\n
In short: AI governance is not a bureaucratic overhead, but a strategic prerequisite for the sustainable and safe use of AI in the company.<\/p>\n
AI governance differs from IT governance primarily in that it addresses specific risks arising from the autonomous, learning, and difficult-to-predict behaviour of AI systems. IT governance regulates the safe and efficient use of information technology in general, while AI governance additionally covers ethical, societal, and regulatory dimensions.<\/p>\n
The following specific differences arise:<\/p>\n
In practice, AI governance complements existing IT governance without replacing it. Both structures should be coordinated with each other to avoid duplication and close gaps.<\/p>\n
Responsibility for AI governance rests at several levels: top management bears overall responsibility and must demonstrate leadership and commitment to the AI management system. Operationally, responsibility is exercised through defined AI roles at the specialist and project level, often consolidated in a function such as the AI Officer.<\/p>\n
Typical roles within an AI governance structure include:<\/p>\n
It is important that these roles and responsibilities are documented in writing and officially assigned to the relevant individuals. Without documented responsibilities, AI governance remains ineffective.<\/p>\n
AI governance is introduced step by step, beginning with an inventory of current AI usage, followed by the development of an AI policy, the assignment of roles, the establishment of a risk management system, and the setting up of monitoring and improvement processes. The structure is guided by the framework of ISO 42001.<\/p>\n
First, the company analyses which AI systems are already in use, which are planned, and which internal and external requirements apply. This includes identifying relevant stakeholders and defining the scope of the AI management system.<\/p>\n
Based on the inventory, top management develops an AI policy that formulates principles for the responsible use of AI. In addition, measurable AI objectives are defined that align with the policy, are communicated, and are reviewed regularly.<\/p>\n
Clear responsibilities are documented in writing. At the same time, the company plans which human, technical, and financial resources are needed for safe AI operation and makes these available.<\/p>\n
A systematic risk assessment is carried out for all relevant AI systems. On this basis, risk treatment measures are defined. For high-risk AI systems within the meaning of the EU AI Act, human oversight mechanisms and logging obligations must additionally be implemented.<\/p>\n
Finally, the company establishes processes for performance evaluation, including internal audits and regular reviews of the AI policy. A documented reporting procedure enables employees to raise concerns about AI systems. Identified weaknesses feed into a continuous improvement process.<\/p>\n
The EU AI Act establishes binding requirements that directly determine how companies must structure their AI governance. In particular, operators of high-risk AI systems face concrete obligations that cannot be fulfilled without a functioning governance structure.<\/p>\n
The key obligations for operators of high-risk AI systems include:<\/p>\n
The AIMS certification under ISO 42001<\/a> offers companies a recognised framework for systematically meeting these legal requirements. Companies that have built an AI management system in line with ISO 42001 are well positioned to demonstrate compliance with the requirements of the EU AI Act. Both frameworks complement each other: the EU AI Act defines the legal minimum, while ISO 42001 provides the structural methodology for implementation.<\/p>\n For companies that are still at the beginning, a gap analysis is recommended as a first step: which requirements of the EU AI Act apply to your own AI systems? Which of these are already covered by existing processes? This analysis forms the basis for a realistic implementation plan.<\/p>\n We at mITSM support specialists, managers, and companies in building the knowledge needed for effective AI governance. As a specialised training provider with more than 20 years of experience in IT management, we offer practical training courses that directly address the requirements of the EU AI Act and ISO 42001.<\/p>\n Our offering in the area of AI governance and AI compliance includes:<\/p>\n Find out more about our training portfolio in the field of AI<\/a> on our website. If you would like to specifically check whether your company already meets the requirements of ISO 42001, find out about our ISO 42001 audit offering<\/a>. Get in touch with us and start your journey towards demonstrably responsible AI governance.<\/p>\n","protected":false},"excerpt":{"rendered":" KI-Governance strukturiert einf\u00fchren: Rollen, Risiken & EU AI Act \u2013 so gelingt der Aufbau Schritt f\u00fcr Schritt.<\/p>\n","protected":false},"featured_media":84886,"parent":0,"menu_order":0,"template":"","tags":[],"knowledge_taxonomy":[3926],"class_list":["post-88653","knowledge","type-knowledge","status-publish","has-post-thumbnail","hentry","knowledge_taxonomy-wissenssammlung-kuenstliche-intelligenz"],"yoast_head":"\nHow mITSM helps you build your AI governance<\/h2>\n
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