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Transparency is considered a key property with respect to the implementation of trustworthy artificial intelligence (AI). It is also addressed in various documents concerned with the standardization and regulation of AI systems. However, this body of literature lacks a standardized, widely-accepted definition of transparency, which would be crucial for the implementation of upcoming legislation for AI like the AI Act of the European Union (EU). The main objective of this paper is to systematically analyze similarities and differences in the definitions and requirements for AI transparency. For this purpose, we define main criteria reflecting important dimensions of transparency. According to these criteria, we analyzed a set of relevant documents in AI standardization and regulation, and compared the outcomes. Almost all documents included requirements for transparency, including explainability as an associated concept. However, the details of the requirements differed considerably, e.g., regarding pieces of information to be provided, target audiences, or use cases with respect to the development of AI systems. Additionally, the definitions and requirements often remain vague. In summary, we demonstrate that there is a substantial need for clarification and standardization regarding a consistent implementation of AI transparency. The method presented in our paper can serve as a basis for future steps in the standardization of transparency requirements, in particular with respect to upcoming regulations like the European AI Act.