Artificial intelligence, digital transformation and green human resource management in Sub-Saharan Africa: a systematic literature review
Nyikiwa Agreement MavundaPurpose
This study aims to systematically review the existing scholarship on the role of artificial intelligence (AI) and digital transformation in enabling green human resource management (GHRM) within Sub-Saharan African (SSA) organisations. Drawing on 58 peer-reviewed articles published between 2018 and 2025, the review addresses two research questions: how AI and digital transformation technologies function as enablers of GHRM in SSA contexts and what contextual factors constrain or moderate their adoption and effectiveness in the region. The study responds to a notable gap in the GHRM literature, which remains disproportionately anchored in the Global North, by foregrounding the distinctive institutional, infrastructural and socio-technical realities of SSA.
Design/methodology/approach
A systematic literature review was conducted following the PRISMA 2020 protocol and the management-domain SLR framework of Tranfield. Thematic content analysis was applied to synthesise findings across the selected corpus. Studies were sourced from Scopus, Web of Science, EBSCO Business Source Complete, ProQuest and Google Scholar and rigorously assessed against structured inclusion and exclusion criteria. Quality appraisal was conducted using an adapted mixed-methods appraisal tool, yielding a final corpus of 58 studies for thematic synthesis.
Findings
AI and digital technologies encompassing big data analytics, cloud computing, AI-driven platforms and mobile learning tools function as multidimensional GHRM enablers in SSA organisations, with the strongest evidence concentrated in green recruitment, mobile-delivered green training and AI-enabled performance monitoring. However, their transformative potential is substantially constrained by an interconnected nexus of digital infrastructure deficits, digital skills gaps and institutional voids that characterise much of the region. The review proposes a contextually extended AMO framework that incorporates digital infrastructure adequacy, organisational AI capability and institutional governance quality as threshold boundary conditions on AI-GHRM effectiveness.
Originality/value
This review makes an original contribution by providing the first systematic synthesis of AI-enabled GHRM scholarship specifically focused on SSA. It integrates decolonial AI theory into GHRM discourse, proposes a contextually grounded theoretical framework with empirically testable propositions and advances a future research agenda focused on longitudinal, comparative and participatory scholarly engagement with one of the world’s most rapidly urbanising and environmentally vulnerable regions.