The digital transformation is more of a reality, and organizations are finding it extremely difficult to cope with the issue of converting high volumes of data into practical and useful intelligence. The present paper is about the promise of Saudi organizations in streamlining the process of strategic decision-making when handling big data. The study is analytical and conceptual and examines synthesis of various sources of information, sophisticated analytical technology and organizational designs required to transform information into intelligence. The paper presents the following concepts to be considered as the key facilitators to effective decision-making data integration, artificial intelligence, governance arrangements, and organizational culture. The findings indicate that Saudi institutions are rapidly adopting big data technology and there are significant gaps in the bits of data, governance, and analytics. The transformation of traditional data management to intelligence-based solutions does not just require a molding of technology but an institutional orientation and capacity development. The study also mentions that the quality of decisions, responsiveness, and strategic alignment is high with firms using integrated data ecosystems and AI-based analytics. As well, the research offers the importance of an integrated strategy that integrates both the technological infrastructure and human and organizational factors. The synthesis of the existing literature that the study offers contributes to enhancing the knowledge of the role that big data can be played in supporting evidence-based decision-making in dynamic and complex environments. The paper closes with strategic recommendations on how to aid in the use of data and intelligence development within Saudi organizations and lead to overall reshaping of the nation. This record archives a peer-reviewed journal article originally published in the Journal of Business Insight and Innovation (JBII), Volume 5, Issue 1, 2026, pp. 67-77. Original publication:https://insightfuljournals.com/index.php/JBII/article/view/73 ISSN (Print): 3006-2284ISSN (Online): 3006-0982
Alam et al. (Mon,) studied this question.