AI and Big Data in Project Risk and Quality Management: Opportunities and Challenges in Pakistan

Abstract

Project Risk and Quality Management (PRQM) has become more complicated with the changing technological environment and the dynamic character of contemporary industries. In Pakistan's industrial economy, organizations encounter more challenges in managing project-related risks and quality outcomes. This research explores the impact of technological readiness on the adoption of advanced data-driven tools into PRQM practices and the influence of organizational support levels on this association. Quantitative research design was employed with data gathered among project managers, IT experts, and quality management staff in major industry sectors including manufacturing, construction, energy, and textiles. Two central variables—technological readiness and the use of data-intensive technologies for PRQM—were investigated in conjunction with the moderating influence of organizational support. Regression analysis findings identify a strong positive impact of technological readiness on the use of such tools. In addition, the role of solid organizational support was discovered to strengthen this association, indicating that infrastructure is not enough without managerial and strategic support. The findings highlight the need for the fusion of digital capability and institutional commitment to reinforce risk management and quality assurance processes. The research concludes with workable recommendations for policy, investment, and leadership involvement in enhancing technological uptake in industrial projects in Pakistan.

Key Words: Quality Management, Project Risk, Technological environmental