Navigating human-AI dynamics: implications for organizational performance (SLR)

Abstract

Purpose

The purpose of this study is to investigate the key characteristics of artificial intelligence (AI) in organizational settings, analyze its capacity to reduce customer service jobs in favor of more advanced roles and analyze its efficacy in candidate screening by emphasizing performance.

Design/methodology/approach

A comprehensive analysis of 40 papers is performed using the PRISMA method based on data from Web of Science, Scopus, Emerald and Google Scholar.

Findings

The findings show optimized human resource management operations such as recruiting and performance monitoring, resulting in increased precision in hiring and decreased employee turnover. Customer service automation redistributes human labor to more intricate positions that need analytical reasoning and empathetic skills.

Practical implications

The study has two key implications. First, AI can streamline customer service, freeing up human workers for more complex tasks. Second, AI may increase candidate screening accuracy and efficiency, improving recruiting outcomes and organizational performance.

Originality/value

The study adds to the current literature by shedding light on the intricate relationships between AI and organizational performance and providing insights into the processes underpinning trust-building in AI technology.

Citation

Khushk, A., Zhiying, L., Yi, X. and Zhang, X. (2024), "Navigating human-AI dynamics: implications for organizational performance (SLR)", International Journal of Organizational Analysis, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOA-04-2024-4456