The Contribution of Artificial Intelligence to Enhancing Operational Efficiency and Innovation in Iraqi Production Companies - An Analytical Study
Keywords:
Artificial Intelligence, Transformation Strategies, General Automotive ManufacturerAbstract
The application of artificial intelligence presents opportunities and challenges for human resources in the sales and marketing department. This study aims to analyze how human resources at the General Company for Automotive Industries in Iraq are dealing with digital transformation in the era of artificial intelligence. The research adopts a qualitative descriptive approach, relying on indepth interviews, observations, and documents. This research contributes to current practices and academic studies on the application of artificial intelligence, highlighting how industrial companies coordinate AI resources and capabilities to drive the digital transformation of the organization, while creating a competitive advantage. The data collected is analyzed using the interactive model approach by (Miles and Huberman .1994), which involves three main stages: data reduction, data display, and conclusion drawing and verification. The findings indicate that AI enhances operational efficiency and service personalization but faces challenges such as employee resistance and a digital skills gap. Continuous training strategies and adaptive AI integration are essential for the successful implementation of this technologyReferences
1. Abdallah, M., Alryalat, A., & Dwivedi, Y. K. (2023). A systematic literature review of
2. Abdallah, M., Alryalat, A., & Dwivedi, Y. K. (2023). A systematic literature review of
3. Aghion, P., Jones, B. F., & Jones, C. I. (2019). 9. Artificial Intelligence and Economic
Growth (pp. 237-290). University of Chicago Press. and functionalities. Journal of
Innovation and Knowledge, 8, Article 100333.
4. and functionalities. Journal of Innovation and Knowledge, 8, Article 100333.
5. Andrea, B., Matteri, D., Montini, E., Gładysz, B., & Carpanzano, E. (2021). An AI adoption
model for SMEs: A conceptual framework. IFAC PapersOnLine, 54(1), 702–708.
https://doi.org/10.1016/j.ifacol.2021.08.082
6. Andrea, B., Matteri, D., Montini, E., Gładysz, B., & Carpanzano, E. (2021). An AI adoption
model for SMEs: A conceptual framework. IFAC PapersOnLine, 54(1), 702–708.
https://doi.org/10.1016/j.ifacol.2021.08.082
7. artificial intelligence in the healthcare sector: Benefits, challenges, methodologies,
8. artificial intelligence in the healthcare sector: Benefits, challenges, methodologies,
9. B. Orchard, C. Yang, and M. Ali,(2004). Innovations in Applied Artificial Intelligence: 17th
International Conference on Industrial and Engineering Applications of Artificial
Intelligence and Expert Systems, IEA/AIE 2004, Ottawa, Canada, May 17-20, 2004.
Proceedings. Berlin: Springer
10. Bokrantz, J., Subramaniyan, M., & Skoogh, A. (2023). Realising the promises of artificial
intelligence in manufacturing by enhancing CRISP-DM. Production Planning and Control.
https://doi.org/10.1080/09537287.2023.2234882
11. C. Bennett and K. Hauser, "Artificial intelligence framework for simulating clinical decisionmaking: A Markov decision process approach", Artificial Intelligence in Medicine, vol. 57,
no. 1, pp. 9-19, 2013
12. Chernyakov, M., Chernyakov, M., & Kapustin, A. (2024). Intelligent systems and
technologies in the field of hotel services. 2024 9th International Conference on Energy
Efficiency and Agricultural Engineering (EE&AE).
13. Demlehner, Q., Schoemer, D., & Laumer, S. (2021). How can artificial intelligenc
14. Dey, P. K., Chowdhury, S., Abadie, A., Yaroson, E. V., & Sarkar, S. (2023). Artificia
15. E. Brynjolfsson and A. McAfee, Race against the machine. Lexington, Mass.: Digital
Frontier Press, 2012.
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