Results-Based Management and AI in Development Practice: Effectiveness and Limitations in India’s Development Sector

Sammanfattning

This thesis examines both the effectiveness and limitations of Results-Based Management (RBM) within India’s development sector and explores the role of integrating Artificial Intelligence (AI) tools into RBM processes. The study, guided by three research questions, investigates the perceived benefits and challenges of RBM from the perspective of practitioners, the organisational and contextual factors affecting RBM deployment and explores how practitioners are engaging with AI within RBM workflows. The research adopts a qualitative approach via six semi-structured interviews with development professionals in India and two key informant interviews. The data was analysed via the lenses of two theoretical frameworks, Diffusion of Innovation theory (Rogers, 2003) and Institutional Isomorphism (DiMaggio and Powell, 1983). The findings reveal that RBM effectiveness depends less on the framework itself and more on how it is used, contextualised, negotiated and adapted within donor-driven environments. Additionally, the results show that practitioners have a positive attitude towards AI but demonstrate limited practical adoption, while organisational readiness, ethical concerns and the compatibility gap between AI use and relational nature of development work emerge as key barriers.