Classification of software-based automation technologies: Derivation of characteristics through an empirical investigation

Software-based automation is becoming increasingly important to execute administrative processes more efficiently. It is characterized by different levels of technology performance. The area of application for software-based automation ranges from individual rule-based tasks requiring human-machine collaboration, to decision-based end-to-end automation performed by an artificial intelligence. Existing approaches found in literature and practice to classify those automation stages only insufficiently define the boundaries between the different technology levels. Due to this heterogeneity, it is often unclear how different technology characteristics affect the working environment of a company. This leads to an unpredictable nature of automation: job creation as an opportunity and job loss as a challenge. In this paper, a literature review shows the current state of research regarding the different classifications of technology levels for software-based automation. Consequently, a comparison of these approaches enables the deduction of relevant criteria and creates a frame for the classification of different automation levels. This framework provides an approach for further research to incorporate the effects into the working environment.