The idea of using visualization technology to enhance the understanding of abstract concepts, like data structures and algorithms, has become widely accepted. Several attempts have been made to introduce a system that levels out the burden of creating new visualizations. However, one of the main obstacles to fully taking advantage of algorithm visualization seems to be the time and effort required to design, integrate and maintain the visualizations.Effortlessness in the context of algorithm visualization is a highly subjective matter including many factors. Thus, we first introduce a taxonomy to characterize effortlessness in algorithm visualization systems. We have identified three main categories based on a survey conducted among CS educators: i) scope, i.e. how wide is the context one can apply the system to ii) integrability, i.e., how easy it is to take in use by a third party, and iii) interaction techniques, i.e., how well does the system support different use cases regularly applied by educators. We will conclude that generic and effortless visualization systems are needed. Such a system, however, needs to combine a range of characteristics implemented in many current AV systems.