The first study „Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study with Medical Students and Professionals“ has appeared in JMIR Formative Research (https://pubmed.ncbi.nlm.nih.gov/35319465/). It examines how different types of perceived identity threats (i.e., threats to professional recognition and threats to professional capabilities) can result in resistance to AI systems. The second study „Radiologists Usage of Diagnostic AI Systems“ (https://link.springer.com/article/10.1007/s12599-022-00750-2) examines how radiologists make sense of AI assessments in clinical practice and how this sensemaking process is influenced by the radiologists' diagnostic self-efficacy. Based on an in-depth case study, the study outlines three sensemaking patterns that help radiologists to make sense of AI assessments that confirm or disconfirm their own judgment and outline how those sensemaking practices influence different usage patterns. The second paper is part of the special issue „A Multi-Perspective Framework for Research on (Sustainable) Autonomous System“ by Roman Beck, Jens Dibbern, and Marin Wiener in the Journal of Business & Information Systems Engineering. Both studies are available for open access.