INVESTIGATING THE IMPACT OF AI ON THE WORKFORCE AND THE FUTURE OF WORK IN THE REGION: A MACHINE LEARNING PERSPECTIVE

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Published: 2025-06-20
DOI: https://doi.org/10.46281/a7zcns96
Keywords:
AI, Future Workforce, Clustering methods, Workforce Opportunities and Risks

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Boumedyen Shannaq
Associate Professor, Management of Information Systems Department, University of Buraimi, Al Buraimi Governorate, Sultanate of Oman
https://orcid.org/0000-0001-5867-3986
Ahmed Alabri
Finance and Administrative Affairs & Supporting Services, University of Buraimi, Al Buraimi 512, Sultanate of Oman
https://orcid.org/0009-0009-9743-211X
V. P. Sriram
Associate Professor, Management of Information Systems Department, University of Buraimi, Al Buraimi Governorate, Sultanate of Oman
https://orcid.org/0000-0002-7105-0713
Oualid Ben Ali
Associate Professor and Acting Head, Computer Science Department, Applied Science University, Kingdom of Bahrain
https://orcid.org/0009-0001-1433-017X

Abstract

This study examines the evolving impact of Artificial Intelligence (AI) on workforce dynamics within a regional context. The analysis of structured data, which includes job positions alongside industry categories, collected from Kaggle.com, AI implementation metrics, automation uncertainty assessments, skill requirements, compensation amounts, and work projection estimates, enables the application of machine learning approaches that generate insights for decision support. The purpose of this study is twofold: to analyze the impact of AI on work structures and identify automated jobs, as well as vulnerable sectors, to inform recommendations that help plan education systems and workforce development. Three clustering approaches, including K-Means and DBSCAN, along with Agglomerative Clustering, were implemented to categorize different jobs based on their AI acceptance levels, automation probability, and pay ranges. The performance analysis, as indicated by silhouette scores, revealed that Agglomerative Clustering generated meaningful clusters at a score of 0.289, while both K-Means and DBSCAN recorded scores of 0.262 and 0.093, respectively. The developed clusters enable researchers to identify vulnerable positions while proposing new career options and uncovering stable competencies, which include digital aptitude as well as emotional capability and troubleshooting abilities. The study directly provides answers to major research questions about how AI affects particular sectors while revealing portable skills across industries. Through the integration of cluster analytics and workforce analytics, this study provides policymakers, educational institutions, and workforce planners with strategic information, enabling a resilient labor market that is prepared for the future.


JEL Classification Codes: O33, J24, J21, C55.

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Article Details

Issue

Vol. 10 No. 4 (2025): Bangladesh Journal of Multidisciplinary Scientific Research

Section

Research Paper/Theoretical Paper/Review Paper/Short Communication Paper
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Author Biographies

Boumedyen Shannaq , Associate Professor, Management of Information Systems Department, University of Buraimi, Al Buraimi Governorate, Sultanate of Oman

Dr. Boumedyen Shannaq is an Associate Professor in Smart Information Systems specializing in Automation and AI, Machine Learning, and Data Analytics. With over 18 years as Faculty member ,Program Chair and IS Expert   , he advances research in Smart Information Systems, Knowledge Management, and HCI. His work integrates AI-driven solutions to enhance education and workplace productivity. 

Ahmed Alabri , Finance and Administrative Affairs & Supporting Services, University of Buraimi, Al Buraimi 512, Sultanate of Oman

Dr. Ahmed Alabri is currently serving as the Deputy Vice Chancellor for Financial and Administrative Affairs (DVCFAASS) at the University of Buraimi (UoB), providing strategic leadership and direction in overseeing the university's financial and administrative operations. Also entrusted with managing budgeting, policy development, compliance, performance monitoring, and fostering strategic relationships with external partners.

V. P. Sriram , Associate Professor, Management of Information Systems Department, University of Buraimi, Al Buraimi Governorate, Sultanate of Oman

Dr. V.P. Sriram is currently working as an Associate Professor in College of Business, University of Buraimi, Sultanate of Oman. He is an International Certified SAP Business One – Functional Consultant and worked as a Team Leader and Senior Functional Consultant in various prime projects in India. Overall He has 18+ yrs of Professional Experience. His breadth of experience includes 14+ years of Academic Teaching Experience in University Level and 4 years of Industry Experience. He has published more 29 research papers in both Scopus and Web of Science indexed International Journals. He has presented research papers in premier institutions in India and Abroad.

Oualid Ben Ali , Associate Professor and Acting Head, Computer Science Department, Applied Science University, Kingdom of Bahrain

Dr. Oualid Ben Ali is an Associate Professor and Acting Head of the Computer Science Department at Applied Science University, Bahrain. With a PhD in Computer Science (2006), he has held leadership roles in quality assurance, accreditation, and training across universities in Oman, Bahrain, and the United Arab Emirates (UAE).

How to Cite

Shannaq , B. ., Alabri , A. ., Sriram , V. P., & Ali , O. B. . (2025). INVESTIGATING THE IMPACT OF AI ON THE WORKFORCE AND THE FUTURE OF WORK IN THE REGION: A MACHINE LEARNING PERSPECTIVE. Bangladesh Journal of Multidisciplinary Scientific Research, 10(4), 1-10. https://doi.org/10.46281/a7zcns96
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References

Abbasi, B. N., Wu, Y., & Luo, Z. (2025). Exploring the impact of artificial intelligence on curriculum development in global higher education institutions. Education and Information Technologies, 30, 547–581. https://doi.org/10.1007/s10639-024-13113-z

Abdalla, A. A. (2025). Navigating AI Adoption Challenges in HRM: Insights from the UAE. In M. U. Tariq & R. P. Sergio (Eds.), Practice, Progress, and Proficiency in Sustainability (pp. 215–232). IGI Global. https://doi.org/10.4018/979-8-3373-1917-9.ch010

Akinwale, O. E., Kuye, O. L., & Doddanavar, I. (2025). Scourge of replacing contemporary work environment with artificial intelligence (AI-dark-side): The role of capacity development in quality of work-life and organisational performance. Journal of Systems and Information Technology, 27(1), 116–145. https://doi.org/10.1108/JSIT-08-2024-0297

Awashreh, R. (2025). Omani Public Governance in the Age of Artificial Intelligence: In K. Wongmahesak, J. Ahmad, & A. Mustanir (Eds.), Advances in Computational Intelligence and Robotics (pp. 137–166). IGI Global. https://doi.org/10.4018/979-8-3693-9286-7.ch007

Azoury, N., & Karam, J. (2025). Innovation and AI Adoption: Middle East’s Path to Economic Growth. In N. Azoury & G. Yahchouchi (Eds.), AI in the Middle East for Growth and Business (pp. 7–25). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-75589-7_2

Bahoo, S., Goodell, J. W., Rhattat, R., & Shahid, S. (2025). Artificial Intelligence in Economics Research: What Have We Learned? What Do We Need to Learn? Journal of Economic Surveys, joes.12694. https://doi.org/10.1111/joes.12694

Broady, K. E., Booth-Bell, D., Barr, A., & Meeks, A. (2025). Automation, artificial intelligence, and job displacement in the U.S., 2019–22. Labor History, 1–17. https://doi.org/10.1080/0023656X.2025.2477153

Burton, S. L. (2024). Cybersecure Futures: Bridging AI, Employment, and the Digital Divide. In D. N. Burrell (Ed.), Advances in Human Resources Management and Organizational Development (pp. 155–204). IGI Global. https://doi.org/10.4018/979-8-3693-8562-3.ch006

Dayalan, P., & Sundaramurthy, B. (2024). Exploring the Implementation and Challenges of AI-Based Fraud Detection Systems in Financial Institutions: A Review. In B. Sundaramurthy & P. Dayalan (Eds.), Advances in Business Information Systems and Analytics (pp. 25–38). IGI Global. https://doi.org/10.4018/979-8-3693-4187-2.ch002

Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254–280. https://doi.org/10.1016/j.techfore.2016.08.019

Gayathri, J., & Mangaiyarkarasi, S. (2024). The Impact of AI Integration on Workforce Dynamics: Legal Challenges and Labour Law Implications in the Era of Business Technology Transformation. In B. Sundaramurthy & P. Dayalan (Eds.), Advances in Business Information Systems and Analytics (pp. 277–300). IGI Global. https://doi.org/10.4018/979-8-3693-4187-2.ch013

Hamdan, R. K. (Ed.). (2025). Sustainable Data Management: Navigating Big Data, Communication Technology, and Business Digital Leadership. Volume 1 (Vol. 171). Springer Nature.

Hassouni, A., & Mellor, N. (2025). AI in the United Arab Emirates’ Media Sector: Balancing Efficiency and Cultural Integrity. Journalism and Media, 6(1), 31. https://doi.org/10.3390/journalmedia6010031

Hazaa, B., & Al Mubarak, M. (2024). Digital Transformation in the Oil and Gas Industry in the GCC: Exploring Opportunities and Addressing Challenges. In M. Al Mubarak & A. Hamdan (Eds.), Innovative and Intelligent Digital Technologies; Towards an Increased Efficiency (Vol. 569, pp. 641–662). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-71649-2_54

Jin, X., & Han, J. (2011). K-Means Clustering. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_425

Karam, J., El Hayek, Z., & Youssef, L. (2025). AI and Cultural Adaptation: Leveraging MENA Values in Business. In N. Azoury & G. Yahchouchi (Eds.), AI in the Middle East for Growth and Business (pp. 61–73). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-75589-7_5

Kaur, H., Reddy, K. K., Reddy, M. K., & Hanafiah, M. M. (2024). Collaborative Approaches to Navigating Complex Challenges and Adapting to a Dynamically Changing World: In B. K. Mishra (Ed.), Advances in Mechatronics and Mechanical Engineering (pp. 209–234). IGI Global. https://doi.org/10.4018/979-8-3693-7076-6.ch010

Kshetri, N., & Sharma, R. S. (2025). Editorial: Development, diffusion, and impact of generative AI in the Gulf Cooperation Council economies. Journal of Global Information Technology Management, 28(1), 1–5. https://doi.org/10.1080/1097198X.2025.2454097

Kumar, P. (2025). Artificial intelligence (AI)-augmented knowledge management capability and clinical performance: Implications for marketing strategies in healthcare sector. Journal of Knowledge Management, 29(2), 415–441. https://doi.org/10.1108/JKM-01-2024-0111

Lamees, A.-Z., & Ramayah, T. (2025). How artificial intelligence-based supply chain analytics enable supply chain agility and innovation? An intellectual capital perspective. Supply Chain Management: An International Journal, 30(2), 233–249. https://doi.org/10.1108/SCM-09-2024-0558

Leveraging Predictive Analytics to Optimize Business Performance and Drive Operational Excellence. (2025). International Journal of Computer Applications Technology and Research. https://doi.org/10.7753/IJCATR1402.1005

Lund, B., Orhan, Z., Mannuru, N. R., Bevara, R. V. K., Porter, B., Vinaih, M. K., & Bhaskara, P. (2025). Standards, frameworks, and legislation for artificial intelligence (AI) transparency. AI and Ethics. https://doi.org/10.1007/s43681-025-00661-4

Nadimpalli, C. S. C., Muttamsetty, L. S., Pamu, R. N., & Teku, K. (2025). The Future of Employment With the Advent of AI: Boon or Bane? In A. Günar (Ed.), Advances in Finance, Accounting, and Economics (pp. 267–296). IGI Global. https://doi.org/10.4018/979-8-3693-7036-0.ch012

Naim, N., AlDebasi, A., & Price, D. (Eds.). (2025). Innovation and development of knowledge societies: Artificial intelligence and knowledge-based socioeconomic growth. Gulf Research Meeting, New York. Routledge.

Nawaz, W., & Li, Z. (2025). Complexity to Resilience: Machine Learning Models for Enhancing Supply Chains and Resilience in the Middle Eastern Trade Corridor Nations. Systems, 13(3), 209. https://doi.org/10.3390/systems13030209

Öztaş, Y. E., & Arda, B. (2025). Re-evaluating creative labor in the age of artificial intelligence: A qualitative case study of creative workers’ perspectives on technological transformation in creative industries. AI & SOCIETY. https://doi.org/10.1007/s00146-025-02180-6

Pandya, B., Patterson, L., & Ruhi, U. (2022). The readiness of workforce for the world of work in 2030: Perceptions of university students. International Journal of Business Performance Management, 23(1/2), 54. https://doi.org/10.1504/IJBPM.2022.119555

R., K. S., & Archana, T. (2025). Artificial Intelligence (AI) and Digital Competencies in the Public Sector: In E. B. Sevinç Çubuk (Ed.), Advances in Public Policy and Administration (pp. 95–120). IGI Global. https://doi.org/10.4018/979-8-3693-6547-2.ch005

Rawashdeh, A. (2025). The consequences of artificial intelligence: An investigation into the impact of AI on job displacement in accounting. Journal of Science and Technology Policy Management, 16(3), 506–535. https://doi.org/10.1108/JSTPM-02-2023-0030

Rojas, L., Peña, Á., & Garcia, J. (2025). AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management. Applied Sciences, 15(6), 3337. https://doi.org/10.3390/app15063337

Sarala, R. M., Post, C., Doh, J., & Muzio, D. (2025). Advancing Research on the Future of Work in the Age of Artificial Intelligence (AI). Journal of Management Studies, joms.13195. https://doi.org/10.1111/joms.13195

Sander, J., Ester, M., Kriegel, HP. et al. Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications. Data Mining and Knowledge Discovery 2, 169–194 (1998). https://doi.org/10.1023/A:1009745219419

Sigafoos, J., Lancioni, G. E., & O’Reilly, M. F. (2025). Assistive Technology Solutions for Enabling People with Intellectual and Motor or Sensory-Motor Disabilities to Access Communication Events. In J. Sigafoos, G. E. Lancioni, & M. F. O’Reilly, Communication Strategies for People with Severe Disabilities (pp. 143–162). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-83807-1_9

Suleiman, A. K., & Ming, L. C. (2025). Transforming healthcare: Saudi Arabia’s vision 2030 healthcare model. Journal of Pharmaceutical Policy and Practice, 18(1), 2449051. https://doi.org/10.1080/20523211.2024.2449051

Tariq, M. U. (2025). AI-Powered Business Process Automation: Revolutionizing Firm Management. In A. M. S. Derbali (2025), Advances in Finance, Accounting, and Economics (pp. 199–224). IGI Global. https://doi.org/10.4018/979-8-3693-7357-6.ch010

Tenakwah, E. S., & Watson, C. (2025). Embracing the AI/automation age: Preparing your workforce for humans and machines working together. Strategy & Leadership, 53(1), 32–48. https://doi.org/10.1108/SL-05-2024-0040

Tharmalingam, L., & Pereira, M. (2025). AI Adoption & Automation Risk. Retrieved from https://www.kaggle.com/datasets/martnpereira/ai-adoption-and-automation-risk-san-francisco-ca

The Future of Work: Embracing AI’s Job Creation Potential. (2025). Retrieved April 4, 2025, from https://www.forbes.com/councils/forbestechcouncil/2024/03/12/the-future-of-work-embracing-ais-job-creation-potential/

The potential impact of Artificial Intelligence in the Middle East—PwC Middle East. (2025). Retrieved from https://www.pwc.com/m1/en/publications/potential-impact-artificial-intelligence-middle-east.html

Unanah, O. V., & Mbanugo, O. J. (2025). Telemedicine and mobile health imaging technologies: Business models for expanding U.S. Healthcare Access. International Journal of Science and Research Archive, 14(2), 470–489. https://doi.org/10.30574/ijsra.2025.14.2.0398

Visvizi, A., Troisi, O., & Grimaldi, M. (Eds.). (2025). ICT, the business sector and smart cities. Routledge.

Wang, K.-H., & Lu, W.-C. (2025). AI-induced job impact: Complementary or substitution? Empirical insights and sustainable technology considerations. Sustainable Technology and Entrepreneurship, 4(1), 100085. https://doi.org/10.1016/j.stae.2024.100085

Zepeda-Mendoza, M. L., & Resendis-Antonio, O. (2013). Hierarchical Agglomerative Clustering. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9863-7_1371

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