Effectiveness of AI in Strategic Decision Making: An Empirical Study on Identifying High-Potential Talents

Abstract

While the efficiency of AI in decision making has been confirmed in the literature, the effectiveness of AI decision making is less studied. To address this research void, we examine the effectiveness of AI using data collected from a leading technology company that applies both AI and human in the high-potential talent identification process. The cross-sectional comparison of these employees’ after-selection performance generates mixed results. While the AI-selected employees had higher contribution scores than their human-recommended peers, the human-recommended employees showed higher growth potential (proxied by promotion speed) and organizational commitment (proxied by turnover). Further analysis indicates that the AI-selected employees exhibited suboptimal performance on all three aspects when compared to the short-listed employees that were selected through an additional round of human evaluation. Jointly, these results suggest that AI can be an effective screening tool for identifying high-potential talents, but human instinct is essential for the final selection