Manuscript Title:

STRATEGIC COST MANAGEMENT THROUGH AI

Author:

Dr. MAZEN MOHAMMED FAREA, Dr. BELAL ALIFAN, HELMI MURAD EBRAHIM AHMED, Dr. MAGED MUSTAFA MAHYOUB AL-DUBAI, Dr. FIRAS RASHED WAHSHEH, Dr. TS. YOUSEF A. BAKER EL-EBIARY

DOI Number:

DOI:10.5281/zenodo.12515104

Published : 2024-06-23

About the author(s)

1. Dr. MAZEN MOHAMMED FAREA - Associate Professor, Faculty of Finance & Administrative Sciences, Al-Madinah International University, Malaysia.
2. Dr. BELAL ALIFAN - Assistant Professor, Faculty of Information Technology Philadelphia University, Jordan.
3. HELMI MURAD EBRAHIM AHMED - Volkshochscule, Munich, Germany.
4. Dr. MAGED MUSTAFA MAHYOUB AL-DUBAI - Associate Professor, Management Development Institute of Singapore in Tashkent, Uzbekistan.
5. Dr. FIRAS RASHED WAHSHEH - Assistant Professor, Department of Management Information Systems, Faculty of Business, Ajloun National University, Ajloun, Jordan.
6. Dr. TS. YOUSEF A. BAKER EL-EBIARY - Professor, Faculty of Informatics and Computing, UniSZA, Malaysia.

Full Text : PDF

Abstract

Introduction: Strategic Cost Management (SCM) has become an essential element for businesses seeking to enhance profitability and maintain competitive advantage. With the advent of artificial intelligence (AI), there are unprecedented opportunities to optimize cost structures, improve efficiency, and drive strategic decision-making. This paper explores the integration of AI into SCM and its potential to transform cost management practices. Problem Statement: Despite the significant advancements in AI, many organizations struggle to effectively incorporate AI technologies into their SCM processes. Challenges include understanding AI applications, aligning AI with strategic goals, and managing the transition from traditional methods to AI-driven approaches. Objective: The objective of this research is to investigate how AI can be leveraged for strategic cost management, identify key areas where AI can have the most impact, and propose a framework for successful implementation of AI-driven SCM. Methodology: This study employs a mixed-methods approach, combining qualitative and quantitative research. A comprehensive literature review is conducted to establish the theoretical foundation. Case studies of companies successfully implementing AI in SCM are analyzed, supplemented by interviews with industry experts. Additionally, a survey is administered to gather data on current practices, challenges, and perceptions of AI in SCM. Results: The research findings indicate that AI significantly enhances cost prediction accuracy, optimizes resource allocation, and improves decision-making processes. Key success factors identified include top management support, clear strategic alignment, and robust data infrastructure. Case studies reveal that companies employing AI in SCM experience notable cost reductions and efficiency gains. Conclusion: AI holds transformative potential for strategic cost management, offering tools and techniques that surpass traditional methods. Organizations that effectively integrate AI into their SCM processes can achieve substantial cost savings and operational efficiencies. The proposed framework provides a practical guide for organizations aiming to leverage AI in their cost management strategies.


Keywords

Strategic Cost Management, Artificial Intelligence, Cost Optimization, Efficiency Improvement, Decision-Making, AI Implementation Framework.