With the increased adoption of artificial intelligence (AI) in industry and society, effective human-AI interaction systems are becoming increasingly important. A central challenge in the interaction of humans with AI is the estimation of difficulty for human and AI agents for single task instances. These estimations are crucial to evaluate each agent\u27s capabilities and, thus, required to facilitate effective collaboration. So far, research in the field of human-AI interaction estimates the perceived difficulty of humans and AI independently from each other. However, the effective interaction of human and AI agents depends on metrics that accurately reflect each agent\u27s perceived difficulty in achieving valuable outcomes. Research to date has not yet adequately examined the differences in the perceived difficulty of humans and AI. Thus, this work reviews recent research on the perceived difficulty in human-AI interaction and contributing factors to consistently compare each agent\u27s perceived difficulty, e.g., creating the same prerequisites. Furthermore, we present an experimental design to thoroughly examine the perceived difficulty of both agents and contribute to a better understanding of the design of such systems
