AI - AUGMENTED LEADERSHIP AND EMOTIONAL INTELLIGENCE MODELLING IN AFRICAN INDUSTRIAL SETTING

Abstract The accelerating convergence of Artificial Intelligence (AI) and organizational leadership is reshaping productivity across industries, yet African contexts remain insufficiently theorized, particularly regarding the integration of AI with human-centred leadership constructs. This paper examined the interface between AI-augmented leadership and Emotional Intelligence (EI) in driving adaptive performance and sustainable competitiveness in African industries. It advances a context-sensitive integrative framework that explains how the synergy between AI capabilities and EI competencies enhances leadership effectiveness. To achieve this aim, the paper evaluated the extent to which AI-augmented analytics improves leaders’ decision-making processes, examined the interaction between EI and AI systems in shaping organizational performance, and developed a framework for implementing AI-augmented emotionally intelligent leadership within African settings. The paper was anchored on Transformational Leadership Theory and Goleman’s Emotional Intelligence framework, offering a dual perspective that integrates technological augmentation with relational competencies. Methodologically, a systematic analytical review approach was adopted, drawing on secondary data to synthesize existing empirical and conceptual insights. Findings indicated that leaders who effectively integrate AI into their practices while demonstrating high EI exhibit greater adaptability, reduced organizational conflict, and improved employee engagement. These outcomes highlight the complementary relationship between AI-driven analytics and emotionally intelligent leadership. The paper concluded that AI is unlikely to replace human leadership; rather, when strategically integrated, it enhances leaders’ effectiveness and emotional capacity. The paper recommended among others that African organizations should institutionalize leadership development programmes that combine AI literacy with emotional intelligence to support data-driven and human-centred decision-making.