This study aims to analyze whether technological changes in the fourth industrial revolution (4IR), as independent variables, can influence employment, a dependent variable. It categorizes scientific technology changes in the 4IR based on related research, and identifies six factors and corresponding research hypotheses. The paths for the six hypotheses were analyzed using 275 effective samples. Results show that life-convenience technology and blockchain technology variables significantly influenced employment (p < 0.001). Additionally, innovation technology, interface technology, human life technology, and 3D technology variables significantly influenced employment (p < 0.01). The power of the total variance explanation (69.596%) for the employment influence was very high. Seven items—self-driving cars, decision-making using big data, Internet of Things, Wearable Internet, Designer Beings, 3D printing technology and human health, and Bitcoin and blockchain—were statistically significant for the employment effect. The study obtained effective paths for the employment influence of fundamental technologies and derived the demographic variable presenting a meaningful difference among groups. This research seeks a policy direction that enables preparation for 4IR deployment. It also contributes to the academic sphere in meaningfully and empirically classifying the technology factors of the 4IR.