Re-engineering the Botswana civil service with human-AI augmentation: A grounded theory of organizational transformation for a Fourth Industrial Revolution-ready public sector

This study investigates the organisational transformations required to re-engineer Botswana’s civil service through human–AI collaboration to develop a Fourth Industrial Revolution–ready public sector. The study adopted a qualitative research design based on document analysis informed by grounded theory principles. Secondary data were drawn from government reports, national and regional policy documents, and peer-reviewed academic literature published between 2020 and 2025. An inductive analytical process involving open, axial, and selective coding was used to identify recurring patterns and relationships, leading to the development of an integrative theoretical explanation of AI-enabled organisational transformation in Botswana’s civil service. The findings demonstrate that effective AI integration in Botswana’s civil service requires fundamental organisational restructuring. In relation to leadership and management, the study finds that adaptive leadership competencies, strategic sense-making, and participatory managerial practices are critical for aligning AI initiatives with public service objectives. With respect to the workforce, the findings reveal that workforce anxiety is a major constraint on AI adoption, but can be mitigated through targeted skills development, transparent communication, and continuous learning frameworks. Across all objectives, the study identifies leadership as the central mediating mechanism through which organisational change, workforce trust, and human–AI collaboration is achieved. Ethical governance and cross-sectoral collaboration further emerge as enabling conditions for sustainable and trusted AI deployment. The study relies exclusively on secondary data, which limits direct insight into the lived experiences of civil servants during AI implementation. Nonetheless, the study offers a robust theoretical contribution by advancing a leadership-mediated model of human–AI augmentation that can inform public sector reform, policy design, and leadership development in Botswana and comparable developing-country contexts.