The adoption of AI for project portfolio management in South African financial services - Chisuro, Kundishora (University of the Witwatersrand, Johannesburg, 2025)
The growing potential of artificial intelligence (AI) to improve project portfolio management (PPM) through better decision making, resource optimisation and strategic alignment is creating new opportunities for the South African financial services sector. This study examines the key technological, organisational and environmental factors influencing the adoption of AI for PPM, filling an important gap in research on emerging markets. Using the Technology-Organisation- Environment (TOE) framework, the study adopts a quantitative, cross-sectional design. Based on a literature review, nine key factors were identified and included in a questionnaire to assess their importance. The data was collected from IT and project management employees in South African financial services organisations. Covariance-based structural equation modelling (CB-SEM) was used to analyse the relationships between these factors and the adoption of AI. The results show that high data quality and a favourable investment environment are the most important factors. Organisational readiness, technological infrastructure, top management support, supportive culture and government regulation also have a positive influence. In contrast, the availability of AI technologies and skilled technical personnel has a negative effect when considered alone, suggesting that these factors may hinder adoption without additional support. Although the study focuses on the South African financial services sector, which may limit the generalisability of the findings, it provides useful insights into the factors driving AI adoption. The findings provide recommendations for financial organisations, IT leaders, project management stakeholders and policy makers to support AI integration, guide strategic decisions and develop frameworks that promote responsible AI adoption while driving innovation. This research contributes to the theoretical understanding of AI adoption for PPM in emerging markets, particularly in South Africa. By applying the TOE framework and CB-SEM, it highlights the importance of an integrated approach considering the interplay of technological, organisational and environmental factors.
A research report submitted in fulfillment of the requirements for the Master of Management in the field of Digital Business, in the Faculty of Commerce Law and Management, Wits Business School, University of the Witwatersrand, Johannesburg, 2025
Keywords: UCTD; Artificial intelligence; Financial services; Project portfolio managemen; SDG-9: Industry, innovation and infrastructure