Impact of Integrated Artificial Intelligence in Human Resource Management Functions

Abstract

The promise and reality of AI in HRM are contrasted, and improvements are suggested. We identify four obstacles to the integration of data science into human resource practices: Complexity of HR phenomena, limitations of limited data sets, ethical issues relating to fairness and regulatory restraints, and employee response to data-based algorithms. We propose practical solutions to these issues and converge on three principles for the application of data analytics to personnel management. These are the causal reasoning, randomization, and process formalization principles.