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

Borah, Subhalaxmi LU and Haroyan, Tatev LU (2026) MIDM19 20261
Department of Human Geography
LUMID International Master programme in applied International Development and Management
Abstract
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... (More)
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. (Less)
Please use this url to cite or link to this publication:
author
Borah, Subhalaxmi LU and Haroyan, Tatev LU
supervisor
organization
course
MIDM19 20261
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Results-Based Management, RBM, Artificial Intelligence, AI integration, development practice, monitoring and evaluation, India, Diffusion of Innovation, institutional isomorphism
language
English
id
9226187
date added to LUP
2026-06-30 14:06:00
date last changed
2026-06-30 14:06:00
@misc{9226187,
  abstract     = {{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.}},
  author       = {{Borah, Subhalaxmi and Haroyan, Tatev}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Results-Based Management and AI in Development Practice: Effectiveness and Limitations in India’s Development Sector}},
  year         = {{2026}},
}