Browsing by Author "CHISHA, Encyla"

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    Perceived Attributes Influencing Stakeholder Attitudes towards the Adoption of Artificial Intelligence in Project Management
    (University of Lusaka, 2025) CHISHA, Encyla
    The integration of artificial intelligence (AI) in project management is transforming various industries, including healthcare, by enhancing efficiency, optimizing resource allocation, and improving decision-making. While AI adoption is growing globally, its implementation in healthcare project management remains limited, particularly in Africa. In Zambia, research on AI adoption has primarily focused on finance, education, and agriculture, leaving a gap in understanding its role in healthcare project management. Existing studies suggest that attitudes toward AI significantly influence adoption decisions, yet little is known about these perceptions within Zambia’s healthcare sector. This study explores the perceived attributes influencing stakeholder attitudes toward AI adoption in healthcare project management, guided by Rogers’ Diffusion of Innovations (DOI) Theory. Specifically, it examines five key factors: relative advantage, compatibility, complexity, trialability, and observability. The research aims to provide insights into facilitators and barriers to AI adoption in Zambia’s healthcare industry. A qualitative research approach was adopted, utilizing purposive sampling and Key Informant Interviews (KIIs) to gain in-depth insights into stakeholder perceptions, experiences, and behaviors regarding AI adoption. The findings highlight significant urban-rural disparities, with urban areas benefiting from better infrastructure and AI integration, while rural regions struggle with resource limitations and reliance on manual processes. The study reveals that relative advantage drives AI adoption through efficiency and accuracy, trialability facilitates acceptance through pilot programs, and observability promotes uptake by showcasing real-world benefits. However, complexity poses challenges such as fears of job displacement, technical difficulties, and workflow disruptions, while compatibility determines AI adoption based on alignment with existing systems and organizational goals. Key policy implications emphasize the need for strategic investments in AI infrastructure, capacity-building, and regulatory frameworks. Recommendations include financial support through subsidies and funding to facilitate AI adoption, policy development on data privacy and security, targeted training programs to equip healthcare professionals with AI-related skills, and pilot projects to demonstrate AI’s practical benefits Strengthening internet connectivity and IT systems, fostering collaborations with technology firms, and promoting knowledge dissemination and advocacy are also crucial for sustainable AI integration. Continuous monitoring and evaluation will be essential to ensure AI’s effectiveness while balancing its integration with traditional healthcare approaches. By addressing these challenges and leveraging AI’s potential, Zambia’s healthcare sector can enhance project management efficiency and improve overall healthcare delivery Key words: Artificial Intelligence (AI), Healthcare Project Management, AI Adoption, Diffusion of Innovations (DOI) Theory, Perceived Attributes, Stakeholder attitudes.