Role of Artificial Intelligence in Cost Reduction and Competitiveness Achievement
DOI:
https://doi.org/10.70062/greeneconomics.v2i1.108Keywords:
AI, Costs, Efficiency, CompetitiveAbstract
The research addresses the role of artificial intelligence technologies in achieving cost reduction, achieving a sustainable competitive advantage, and improving the operational performance of companies, by analyzing how these technologies reduce costs. The research is based on a basic hypothesis that "artificial intelligence technologies contribute positively to reducing costs for economic units by improving the efficiency of using available resources, reducing waste, and improving technical innovations, which enhances the ability of the economic unit to compete and achieve a sustainable competitive advantage." The research recommends investing in artificial intelligence technologies, training employees to use them effectively, developing a clear strategy, adopting analytical models to measure the impact of artificial intelligence on performance and costs on a regular basis, and supporting research related to developing artificial intelligence applications to improve operational efficiency and enhance cooperation between universities and economic units to develop innovative solutions that achieve a sustainable competitive advantage. This research is an addition to the literature concerned with how economic units adopt artificial intelligence technologies and work to reduce their operating costs, and aims to provide a practical framework for economic units seeking to improve their financial performance by adopting the latest artificial intelligence technologies.
References
Abu Bakr, M. (2004). Human resources: An introduction to achieve competitive advantage. Cairo: Al-Jamiaa Press.
Al-Aqoor, S.M. (2022). Effect of AI on cost reduction in Jordanian industrial companies listed on Amman stock exchange. Unpublished Master's Thesis, World Islamic Science and Education University, Jordan.
Al-Jaber, G.M. (2020). Impact of AI on the efficiency of accounting systems in Jordanian banks. Master's Thesis, Middle East University, Jordan.
Al-Maqiti, S.A.H. (2021). The Reality of Employing Artificial Intelligence and Its Relationship to the Quality of Performance of Jordanian Universities from the Faculty’s Perspectives. Master's Thesis, Middle East University, Jordan.
Ashehri, R. (2019). Governance of artificial intelligence in KSA: Neom as model. International Journal of Advanced Studies, 46-80.
Bilaly, A. (2007). Competitive advantage in economic businesses between private resources and external environment: A case study of Algeria's telecommunication enterprises. PhD Dissertation, Algiers University, Algeria.
Bouzaid, A. (2017). Role of expert systems in the quality of higher administration decision-making in the Palestinian Ministry of Health. Master's Thesis, Al-Aqsa University, Palestine.
Business School (2023). University of Central Florida. www.bus.ucf.edu
Erqal, M. & Ibraheem, A.M. (2023). Accounting of resource use and its role in cost management: A survey. Arab Journal of Human and Social Studies, 33(1).
Estep, C., Griffith, E.E., & MacKenzie, N.L. (2023). How do financial executives respond to the use of artificial intelligence in financial reporting and auditing? Review of Accounting Studies, 1-34.
Fisher, I.E., Garnsey, M.R., & Hughes, M.E. (2016). Natural language processing in accounting, auditing, and finance: A synthesis of the literature with a roadmap for future research. Intelligent Systems in Accounting, Finance, and Management, 23(3), 157-214.
Gamoura, S.C., Bay, M., & Kerrouche, H. (2018). AI between reality and hope. A technical field study. The International Conference on Artificial Intelligence: A Challenge to Laws? Hasiba Bouali University, Algeria, November, 2018.
Jeannie, F. (2012). Exploring boundaries: Optimizing individual class boundaries for binary classification problem. Proceedings of the 14th annual conference on Genetic and evolutionary computation.
Kang, Y., Cai, Z., Tan, C.W., Huang, Q., & Liu, H. (2020). Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics, 7(2), 139-172.
Khaira, T. (2015). Role of artificial intelligence in the achievement of sustainable competitive advantage: A case study of Mobilis telecom in Ain Defla. Master's Thesis, Djilali Bounaama University, Algeria.
Mousa, A. & Bilal, A.H. (2019). AI: A revolution in modern technologies. Kitab Inc.
Nunnally, J.C. & Bernstein, I.H. (1994) The assessment of reliability. Psychometric Theory, 3, 248-292.
Parry, J., Palaz, D., Clarke, G., Lecomte, P., Mead, R., Berger, M., & Hofer, G. (2020). Analysis of Deep Learning Architectures for Cross-Corpus Speech Emotion Recognition. Interspeech 2020.
Raqeeq, A. (2015). Using AI applications in the management of corporate activities: A case study of selected economic institutions. Master's Thesis, Algeria.
Reisenhofer, C. (2021). Die Anwendung von künstlicher Intelligenz bei unternehmensbezogenen Entscheidungen. Master's Thesis, Graz University, Austria.
Shanaby, S. (2016). Implementation of railway transport development in Algeria using smart transport systems as an AI technique. Journal of Accounting and Finance Studies, 7(1)
Szabadföldi, I. (2021). Artificial intelligence in military application: Opportunities and challenges. Land Forces Academy Review, 26(2), 157-165.
Tang, V.W. (2018). Wisdom of crowds: Cross‐sectional variation in the informativeness of third‐party‐generated product information on Twitter. Journal of Accounting Research, 56(3), 989-1034.
Url, L.M. (2022). Forecasting mit künstlicher intelligenz. Graz University, Austria.
Weber, F. (2020). Künstliche intelligenz für business analytics. Springer Fachmieden Wiesbaden.
