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Artificial Intelligence (AI) has now established itself as a tool for both private and professional use and is omnipresent. The number of available AI systems is constantly increasing and the underlying technologies are evolving rapidly. On an abstract level, most of these systems are operating in a black box manner: only the inputs to and the outputs of the system are visible from outside. Moreover, system outputs often lack explainability, which makes them difficult to verify without expert knowledge. The increasing complexity of AI systems and poor or missing information about the system make an assessment by eye as well as assessing the system’s trustworthiness difficult. The goal is to empower stakeholders in assessing the suitability of an AI system according to their needs and aims. The definition of the term transparency in the context of AI systems represents a first step in this direction. Transparency starts with the disclosure and provision of information and is embedded in the broad field of trustworthy AI systems. Within the scope of this paper, the Federal Office for Information Security (BSI) defines transparency of AI systems for different stakeholders. In order to keep pace with the technical progress and to avoid continuous renewals and adaptions of the definition to the current state of technology, this paper presents a technology-neutral and future-proof definition of transparency. Furthermore, the presented definition follows a holistic approach and thus also takes into account information about the ecosystem of an AI system. In this paper, we discuss our approach and proceeding as well as the opportunities and risks of transparent AI systems. The full version of the paper includes the connection to the transparency requirements in the EU AI Act of the European Parliament and council.