The Impact of Artificial Intelligence on Project Management: A Case Study of (Saudi Aramco)

Abstract

With the field of project management (PM) becoming increasingly focused on AIdriven software, companies can gain ample advantages – but only if the risks are suitably addressed (Kerzner, 2022). Embracing AI within PM means mechanising simple managerial tasks to perform complicated tasks like modelling and resource allotment. Considering AI’s varied benefits, businesses are discovering how to execute AI within their PM activities (Zhang, Wu & Shen, 2020). Adopting AI in PM has radically transformed the manner organizations strategize, implement and manage their project initiatives. Through mechanizing repeated tasks, interpreting large datasets, and improving decision-making skills, AI is shaping the future of PM (Rodrigues & Penedo, 2022). Integrating AI into PM is suitable for large companies such as Saudi Aramco, a global leader in energy that is well-recognized for its complicated and capital-intensive projects. Headquartered in Dhahran, Saudi Arabia, it is the world’s leading integrated energy and chemical organization and is known for its extensive infrastructure projects, including oil refineries, petrochemical plants, and sustainable energy projects (Saudi Aramco, n.d.). As the level and complication involved in such projects demand creative PM tools, the use of AI technologies is a sensible decision. The company is committed to adopting high-tech techniques, making it a perfect choice for this case study research proposal. The motivation for this topic comes from the progressive nature of AI in optimizing project deliverables and the opportunity to discover its relevance in a high-stakes, realworld landscape. Since worldwide energy organizations are increasingly scrutinized regarding cost-effectiveness and sustainability, PM innovations such as AI are both beneficial and important (PMI, 2021). This proposal seeks to assess how Saudi Aramco uses AI to deal with PM challenges like resource allotment, risk evaluation and performance supervision. This case study can generate insightful knowledge on the broad impacts of AI in PM for the energy industry and elsewhere.