During the coming decades we will see a massive evolution of large, generic and „small, specific“ AI models for all kinds of purposes which will especially be true when we have solved the data sovereignty challenge, i.e. when data and model providers can be sure to get the credits for what they are offering. To a large extent these models will cover human knowledge and heritage requesting a completely different attitude to data as we are used to. Persistence and clear identification will be a requirement to exactly know which model is meant and how it was generated. Transparency is of great relevance to know where data came from and who processed them. Accountability of all actors involved will become a requirement, since humans will be increasingly dependent on the correctness of models. Proven and lean data infrastructures with certified processes willneed to guarantee accountabiility. FAIRness in the sense of machine actionability will remain important. FAIR Digital Objects will be the basic building block in these infrastructures and dataspaces that have a chance to improve sovereignty, transparency, accountability and persistence.