AI Cases’ Implications for the Talent Management of Digital Leaders—A Qualitative Content Analysis of Cases

Abstract

This article explores how organizational applications of Artificial Intelligence (AI) impact digital leadership (DL) roles and the corresponding competencies and which approaches in Talent Management (TM) are needed to develop these. There is a gap in the literature regarding the dilemma faced by TM in filling talent pools for the key position of digital leaders, while competence requirements remain vague and distorted by the rapid changes driven by digital transformation. Based on a structured review of the current scientific literature, 72 cases from the European context, encompassing diverse industries and various corporate functions, are qualitatively analyzed to identify hurdles, success factors, and required behavior and subsequent competencies. The cases emphasize applying a step-by-step approach in organizations’ current digital transformation in the European context. Success factors highlight the importance of (digital) leaders equipped with manifold competencies. TM must broaden its scope when identifying leadership talent and become more inclusive. Individual learning journeys are a prerequisite for filling talent pools and, consequently, DL roles. This study represents the exploration into the implications for TM by analyzing DL and the requisite competences in AI applications within organizations. By capturing a current snapshot of DL, the study provides new insights into the necessary competencies and their implications for the future of TM.