Virtual Heritage exhibitions aim to engage a diverse audience through the integration of Virtual Reality and various AI technologies, including Artificial Agents, and Knowledge Graphs. Understanding the nuances of human-agent interactions is crucial to fully harness the potential of these technologies and deliver personalized and captivating experiences. Evaluating the alignment of Virtual Heritage applications with the vision of Hybrid Intelligence – where humans and machines collaborate toward a common goal – presents a significant challenge. In this paper, we investigate the assessment of Hybrid Intelligence within the Virtual Heritage domain using Knowledge Engineering methods. Through the analysis of six different scenarios presented as workflows of tasks and input/output data, we identify and compare classical Knowledge Engineering tasks with HI-specific tasks to measure the level of HI-ness achieved. Our study focuses on evaluating the synergy achieved by mixed teams during various tasks as a measure of HI-ness. The findings provide insights into the effectiveness of Knowledge Engineering to identify HI aspects within existing applications, the potential for quantifying and improving HI-ness in an application, and the identification of modeling limitations.