Developing Talents vis-à-vis Fourth Industrial Revolution

Abstract

The growing numbers of unemployment raises concerns around the world. With the arrival of the Fourth Industrial Revolution (4IR) many believed that 4IR might increase the unemployment rate by replacing the current jobs with automated machines such as robots whereas some argued that 4IR might reduce the unemployment rate by creating millions of new jobs. The paper aims to share the scenario of Industry 4.0 processes that affect future talent management, in determining which jobs will be severely affected, and that will be less affected. The talent mapping is a conceptual framework of job landscapes and the following four clusters examine job characteristics: machine-centric to human-centric, routine to complex, and optimization to identity. A qualitative method was deployed to extracts primary data from educators' perspectives in developing talents required for 4IR through Education 4.0. The adoption of Education 4.0 will be advantageous for developing talent in keeping up with the progressive and demanding talents in 4IR. The proposed model defined that clusters of machine-centric are jobs performed routinely on an application basis and usually structured and do not require any compassion or emotions. While developing talents for clusters in human-centric jobs, it may be difficult to replace humans due to complexities in the decision-making process and required compassion for task completion.