Artificial Intelligence-Enabled Monitoring, Evaluation and Performance Management in Zimbabwe's Public Sector: Implications for Public Sector Innovation and Digital Governance

Artificial Intelligence (AI) has emerged as a transformative digital technology capable of revolutionising public administration through enhanced evidence-based decision-making, improved organisational performance, and strengthened public accountability. As governments worldwide pursue digital transformation to improve service delivery and governance effectiveness, AI-enabled Monitoring and Evaluation (M&E) and Performance Management (PM) systems are increasingly recognised as strategic tools for supporting data-driven policy implementation. Despite growing global adoption, empirical evidence on the application of AI within monitoring and evaluation systems in developing countries, particularly Zimbabwe, remains limited. This study investigates the influence of Artificial Intelligence technologies on monitoring, evaluation, and performance management within Zimbabwe's public sector and examines their implications for public sector innovation and digital governance. Guided by the Technology Acceptance Model and the Information Systems Success Model, the study employed a quantitative research design involving Monitoring and Evaluation and Strategic Policy personnel drawn from central government institutions. Using Cochran's sampling framework, 234 respondents were selected, and 222 valid questionnaires were analysed, representing a 95% response rate. Descriptive statistics, correlation analysis, and multiple regression analysis were conducted using SPSS. The findings demonstrate that machine learning, predictive analytics, natural language processing, robotic process automation, and intelligent dashboards significantly improve monitoring effectiveness, analytical capability, evidence generation, organisational learning, and performance management outcomes. Predictive analytics emerged as the strongest predictor of organisational performance, while institutional readiness significantly moderated successful AI implementation. The study concludes that AI has the potential to transform Zimbabwe's public sector from reactive performance monitoring towards predictive, evidence-driven governance. The paper contributes to the growing literature on AI-enabled public sector innovation by providing empirical evidence from a developing-country context and proposes a strategic framework for integrating AI into government monitoring and evaluation systems. The study recommends the development of a comprehensive national AI governance strategy, investments in digital infrastructure and human capital, strengthened data governance frameworks, and phased implementation of AI technologies to support Zimbabwe's Vision 2030 and broader digital governance agenda.