Leveraging Artificial Intelligence for Big Data Analysis: Enhancing Administrative Processes and Service Delivery in the Private Sector – A Case Study of SABIC

This study seeks to explore the effect of employing artificial intelligence (AI) techniques in the analysis of big data within managerial contexts, focusing on their role in enhancing administrative operations and service delivery in private sector organizations, with SABIC (www.sabic.com/en) serving as a case example. A descriptive survey design was adopted, and data were gathered through a questionnaire administered to a sample of 50 employees— comprising 30 males and 20 females—selected through a convenience sampling method. The outcomes of the research revealed that the implementation of AI techniques for analyzing big data within the managerial context at SABIC had a notably strong impact on enhancing administrative operations and the quality of services provided. From the viewpoint of the employees who participated in the study, the influence of AI integration was perceived as substantial and beneficial across multiple aspects of the organization’s internal processes. Moreover, the statistical analysis demonstrated that there were no significant differences at the 0.05 level in the participants' overall attitudes toward the use of AI for big data analysis and its effect on improving both administrative efficiency and service delivery—when responses were categorized by gender (male vs. female). This indicates a generally shared perception among employees, regardless of gender, regarding the positive value of AI in modernizing administrative functions. However, further examination of the data uncovered statistically significant gender-based differences in specific dimensions, particularly in how AI contributes to enhancing administrative processes. Based on these findings, the study recommends several strategic actions: First, promoting a stronger organizational culture around AI, especially in the field of administrative work. Second, leveraging AI tools and systems as part of talent acquisition and managerial decision-making processes at SABIC. Third, encouraging departments and employees to adopt AI applications by offering training workshops and awareness campaigns that emphasize the practical benefits of AI in improving work performance and service efficiency.

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Publication Details

Journal
American Journal of Business Science Philosophy (AJBSP)
Published
2025-09-26
DOI
https://doi.org/10.70122/ajbsp.v2i2.43
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Leveraging Artificial Intelligence for Big Data Analysis: Enhancing Administrative Processes and Service Delivery in the Private Sector – A Case Study of SABIC

Fawaz Al-Mutairi, Abdullah Al-Saadoun
American Journal of Business Science Philosophy (AJBSP)
Big Data and Business Intelligence
article

Leveraging Artificial Intelligence for Big Data Analysis: Enhancing Administrative Processes and Service Delivery in the Private Sector – A Case Study of SABIC

Fawaz Al-Mutairi, Abdullah Al-Saadoun
article en

Abstract

This study seeks to explore the effect of employing artificial intelligence (AI) techniques in the analysis of big data within managerial contexts, focusing on their role in enhancing administrative operations and service delivery in private sector organizations, with SABIC (www.sabic.com/en) serving as a case example. A descriptive survey design was adopted, and data were gathered through a questionnaire administered to a sample of 50 employees— comprising 30 males and 20 females—selected through a convenience sampling method. The outcomes of the research revealed that the implementation of AI techniques for analyzing big data within the managerial context at SABIC had a notably strong impact on enhancing administrative operations and the quality of services provided. From the viewpoint of the employees who participated in the study, the influence of AI integration was perceived as substantial and beneficial across multiple aspects of the organization’s internal processes. Moreover, the statistical analysis demonstrated that there were no significant differences at the 0.05 level in the participants' overall attitudes toward the use of AI for big data analysis and its effect on improving both administrative efficiency and service delivery—when responses were categorized by gender (male vs. female). This indicates a generally shared perception among employees, regardless of gender, regarding the positive value of AI in modernizing administrative functions. However, further examination of the data uncovered statistically significant gender-based differences in specific dimensions, particularly in how AI contributes to enhancing administrative processes. Based on these findings, the study recommends several strategic actions: First, promoting a stronger organizational culture around AI, especially in the field of administrative work. Second, leveraging AI tools and systems as part of talent acquisition and managerial decision-making processes at SABIC. Third, encouraging departments and employees to adopt AI applications by offering training workshops and awareness campaigns that emphasize the practical benefits of AI in improving work performance and service efficiency.

American Journal of Business Science Philosophy (AJBSP)
Majmaah University (SA)
Openalex Percentile: Top 57%
Big Data and Business Intelligence
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