Artificial Intelligence and Human Resources Management in Cameroon’s Public Sector

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

The use of AI in African public human resource management (HRM) is still a largely unexplored area. This sequential mixed-methods study takes a closer look at how AI is accepted within Cameroon’s Ministry of Public Works (MINTP), drawing on 32 interviews analyzed with NVivo and 653 questionnaires processed through structural equation modeling (SEM). On the theoretical side, this paper breaks new ground by blending the Technology Acceptance Model (TAM) and the Resource-Based View (RBV) with the idea of digital discretion. It introduces the fresh concept of ‘reserve discretion,’ which refers to the right of human appeal acting as a sort of a posteriori human veto. The qualitative results show that people are generally okay with AI handling routine, standardized tasks but are much less comfortable when it comes to decisions requiring human judgment. Meanwhile, the structural equation analysis reveals that psychological factors like concerns over traceability and loss of control pose much bigger obstacles to AI adoption than technical infrastructure issues. Ultimately, having a clearly defined right to human appeal plays a major role in encouraging users to adopt AI, supporting a model of hybrid public governance.