for Saudi Arabia’s Vision 2030
FEATURED PAPER
By Majid Alhajri and Bob Prieto
Saudi Arabia and USA
This paper aims to address the knowledge gap on integrating Artificial Intelligence (AI) in Project Management Offices (PMOs) dealing with the fast-paced socio-economic changes of the Saudi Vision 2030. This study focuses on empirical, field-based data on Saudi project management specialists. It analyzes how AI technologies can help enhance project control, portfolio visibility, and executive decision-making. This study presents the AI-Enabled Strategic PMO Framework (AISPF) to help organizations implement innovative PMO models that will shift the focus of PMOs from back-office to strategic value-add functions.
Introduction
The Kingdom of Saudi Arabia is attempting one of the largest economic and societal shifts in history with Saudi Vision 2030. The Vision 2030 plan outlines a significant amount of large and complex mega-programs and projects that will transform Saudi Arabia. Within that arena, the Project Management Office (PMO) takes on the main functions of governance, control, and strategic fit.
Increased capital deployment will require more agile management frameworks and approaches. In more resource-constrained environments, local project governance is beginning to leverage AI to enhance delivery within a budget and reduce the time of delivery. Within the GCC region, little empirical research has been conducted on this topic. This paper will outline an approach grounded in local research and type up validated AI frameworks that will support the PMO in addressing Saudi Arabia’s national economic challenges and improving strategic fit within the available funding.
Foundations
Modern project management studies show how project governance can be enhanced through AI’s capabilities of forecasting, decision making, risk analysis, and data management. Within the project management field, AI’s main opportunities lie in planning, measurement of performance, management of uncertainty, scheduling, and making predictive decisions (Taboada et al., 2023; Nenni et al., 2025). Müller et al. (2024) additionally identify the increase in AI use by organizations as a trend, and similarly, address the need for more empirical research as a challenge, in the context of projects.
AI-based forecasting, scheduling, risk assessment, and decision-support systems have the potential to improve a project organization’s ability to anticipate and assess deviations and help facilitate more timely management interventions (Taboada et al., 2023; Hashfi & Raharjo, 2023; Nenni et al., 2025). Although a considerable amount of research has been done in this field, empirical evidence and standardized approaches for the incorporation of AI in project management is still lacking and is particularly relevant to the large public and semi-government organizations managing significant capital portfolios and accelerated national transformation programs (Müller et al., 2024; Nenni et al., 2025). This is especially relevant to public and semi-government organizations in Saudi Arabia and the larger GCC, where empirical research is limited and gives this study its focus.
Framework
Adopting a post-positivist research approach, this study assessed primary data collected using a structured, 40-item, Likert-scale survey administered to project management practitioners in Saudi Arabia. Within a consequential validity context, this study examined the impact of the adoption of AI technology on reporting and influencing ’bottom up’ the scheduling, forecasting and risk management; ’top down’ AI technology on decision making and governance and ’across the board’ technology on transparency and performance, value and satisfaction of stakeholders, and project management. Multivariate linear regression framed statistical modeling along with checks of internal consistency and descriptive statistics for the confirmation of operational vectors of the localized project delivery performance driven by technology.
More…
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How to cite this paper Alhajri, M and Prieto, R. (2026) An AI-Enabled Strategic PMO Framework for Saudi Arabia’s Vision 2030, PM World Journal, Vol. XV, Issue IX, September 2026. Available online at https://pmworldjournal.com/wp-content/uploads/2026/09/pmwj168-Sep2026-Alhajri-Prieto-AI-Enabled-PMO-Framework-for-KSA-Vision-2030.pdf
About the Authors
Majid Alhajri
Dar Al Riyadh, Riyadh,
Kingdom of Saudi Arabia
Majid Alhajri is a senior PMO executive with over 20 years of experience leading strategic portfolios, enterprise PMOs, and complex infrastructure and transformation programs across Saudi Arabia. He specializes in PMO establishment, portfolio governance, project controls, and aligning program delivery with organizational strategy and Vision 2030.
As Director of PMO Services at Dar Al Riyadh, Majid leads multidisciplinary teams delivering PMO consulting and program management services for major government and private-sector clients. He is recognized for improving governance, strengthening executive decision-making, and delivering measurable business value through structured portfolio and program management.
Majid is also the author of the AI-Enabled Strategic PMO Framework (AISPF), developed through research on the impact of Artificial Intelligence on PMO performance, demonstrating how AI can enhance governance, strategic alignment, and organizational performance.
He can be contacted at eng.majid@hotmail.com , majid.alhajri@daralriyadh.com
Bob Prieto
Strategic Program Management LLC
Jupiter, Florida, USA
Bob Prieto is Chairman & CEO of Strategic Program Management LLC focused on strengthening engineering and construction organizations and improving capital efficiency in large capital construction programs. Previously, Bob was a senior vice president of Fluor, focused on the development, delivery, and turnaround of large, complex projects worldwide across all of the firm’s business lines; and Chairman of Parsons Brinckerhoff, where he led growth initiatives throughout his career with the firm.
Bob’s board level experience includes Parsons Brinckerhoff (Chairman); Cardno (ASX listed; non-executive director); Mott MacDonald (Independent Member of the Shareholders Committee); and Dar al Riyadh Group (current)
Bob consults with owners of large, complex capital asset programs in the development of programmatic delivery strategies encompassing planning, engineering, procurement, construction, financing, and enterprise asset management. He has assisted engineering and construction organizations to improve their strategy and execution and has served as an executive coach to a new CEO. He is author of eleven books, over 1000 papers and National Academy of Construction Executive Insights, and an inventor on 4 issued patents.
Bob’s industry involvement includes the National Academy of Construction and Fellow of the Construction Management Association of America (CMAA). He serves on the New York University Tandon School of Engineering Department of Civil and Urban Engineering Advisory Board and New York University Abu Dhabi Engineering Academic Advisory Council and previously served as a trustee of Polytechnic University. He has served on the Millennium Challenge Corporation Advisory Board and ASCE Industry Leaders Council. He received the ASCE Outstanding Projects and Leaders (OPAL) award in Management (2024). He was appointed as an honorary global advisor for the PM World Journal and Library.
Bob served until 2006 as one of three U.S. presidential appointees to the Asia Pacific Economic Cooperation (APEC) Business Advisory Council (ABAC). He chaired the World Economic Forum’s Engineering & Construction Governors and co-chaired the infrastructure task force in New York after 9/11. He can be contacted at rpstrategic@comcast.net.
