Digital twins drive the digitization of industrial value chains, the goal of Industry 4.0. While digital twins are only a concept, with the Asset Administration Shell (AAS) a standard has been published which describes a concrete meta-model and interfaces for AAS digital twins. As the AAS standard and the corresponding ecosystem are growing at rapid pace, novel methods for quality assurance are required to maintain interoperability between all components of the ecosystem and to keep up with the high pace. Therefore, in this work, we survey different methods for the automated generation of AAS instances for testing. Here, we focus on fuzzing approaches, as they require the least manual effort and offer a high degree of automation and coverage. We evaluate their applicability in the context of the AAS resulting in a set of recommendations for their future usage in the AAS community.