Implementation of Artificial Intelligence in Operations Management: Opportunities and Challenges for Business

Authors

  • Muhammad Hanif Anshari Universitas Teknologi Yogyakarta

Keywords:

Artificial Intelligence, Operations Management, Business Management, Sharia Management

Abstract

This study aims to examine the implementation of Artificial Intelligence (AI) in operations management by identifying the opportunities it provides for improving operational efficiency, decision-making, productivity, and business performance, as well as the challenges organizations face during its implementation. This study employs a qualitative approach using a literature review method. Relevant scientific literature on Artificial Intelligence, operations management, business processes, automation, and organizational transformation was reviewed and analyzed thematically to identify key patterns regarding the opportunities and challenges associated with AI implementation in business operations. The findings indicate that AI implementation provides significant opportunities for businesses, particularly in process automation, demand forecasting, inventory management, resource optimization, operational decision-making, and customer service. AI can also support organizations in improving efficiency and responding more rapidly to changes in market conditions. However, its implementation is accompanied by several challenges, including high implementation costs, data quality and availability, cybersecurity and privacy risks, employee resistance, lack of AI-related skills, and ethical concerns. The findings suggest that successful AI implementation in operations management requires not only technological readiness but also organizational preparedness, employee competence, effective data governance, and appropriate managerial strategies.

References

Alderete, M. V. (2025). Artificial intelligence adoption dynamics and knowledge in SMEs and large firms: A systematic review and bibliometric analysis. Journal of Innovation & Knowledge, 10, 100682.

Ariani, F. G., Herawati, E., & Al Farisi, M. S. (2025). The Effect Of Sharia Marketing Through Social Media On Purchasing Decisions Gardenia Bogor Housing. Ad-Deenar: Jurnal Ekonomi dan Bisnis Islam, 9(02), 209-224.

Bresciani, S., Ferraris, A., Romano, M., & Santoro, G. (2025). Artificial intelligence and digital transformation in organizations: Opportunities, challenges, and implications for business. Applied Sciences, 15(12), 6465.

Culot, G., Podrecca, M., & Nassimbeni, G. (2024). Artificial intelligence in supply chain management: A systematic literature review of empirical studies and research directions. Computers in Industry, 162, 104132.

Inayatulloh, I., Hartono, I. K., Fachrul, A. F., Al Farisi, M. S., Sriwardiningsih, E., & Fachri, R. M. F. (2022). Blockchain technology for customer protection in e-commerce transactions. Journal of Cybersecurity, 1(1), 1-12.

Jia, F., Shahzadi, G., & Chen, L. (2024). AI adoption in supply chain management: A systematic literature review. Journal of Manufacturing Technology Management, 35(6), 1125–1150.

Kumar, N., & Kumar, R. R. (2025). Human–AI collaboration in operations and supply chain management: A systematic literature review. Management Review Quarterly.

Lee, M. C. M., Scheepers, H., Lui, A. K. H., & Ngai, E. W. T. (2023). The implementation of artificial intelligence in organizations: A systematic literature review. Information & Management, 60(5), 103816.

Liu, Q., Ma, Y., Chen, L., Pedrycz, W., Skibniewski, M. J., & Chen, Z.-S. (2024). Artificial intelligence for production, operations and logistics management in modular construction industry: A systematic literature review. Information Fusion, 109, 102423.

Logožar, K. (2024). The role of Artificial Intelligence in Supply Chain Management: A systematic literature review. ENTRENOVA – Enterprise Research Innovation Journal.

Martuscelli, L., Fantozzi, I. C., Leoni, L., & Schiraldi, M. M. (2026). Artificial intelligence for operational excellence in operations management: A systematic literature review and classification framework in manufacturing. Production Planning & Control.

Oktavia, N. F., Herawati, E., & Al Farisi, M. S. (2025). Marketing Strategy Analysis In Increasing Sales At Fayza Busana Cileungsi (Shariah Economic Perspective). Profit: Jurnal Kajian Ekonomi dan Perbankan Syariah, 9(1), 167-179.

Oldemeyer, L., Jede, A., & Teuteberg, F. (2025). Investigation of artificial intelligence in SMEs: A systematic review of the state of the art and the main implementation challenges. Management Review Quarterly, 75, 1185–1227.

Pereira, V., et al. (2025). Impact of generative artificial intelligence on workload, efficiency and labour productivity. IFAC-PapersOnLine, 59(10), 1408–1413.

Putri, S. J. S. D., Al Farisi, M. S., & Herawati, E. (2025). Transparansi Dan Electronic Word Of Mouth (E-Wom): Minat Generasi Z Membayar Zakat Melalui Platform Online. RIGGS: Journal of Artificial Intelligence and Digital Business, 4(2), 2059-2069.

Samuels, A. S. (2025). Examining the integration of artificial intelligence in supply chain management from Industry 4.0 to 6.0: A systematic literature review. Frontiers in Artificial Intelligence, 7.

Shahzadi, G., Jia, F., & Chen, L. (2024). AI adoption in supply chain management: A systematic literature review. Journal of Manufacturing Technology Management, 35(6), 1125–1150.

Shalpegin, T., Browning, T. R., Kumar, A., Shang, G., Thatcher, J., Fransoo, J. C., Holweg, M., & Lawson, B. (2025). Generative AI and empirical research methods in operations management. Journal of Operations Management, 71(5), 578–587.

Spreitzenbarth, J. M., Bode, C., & Stuckenschmidt, H. (2024). Artificial intelligence and machine learning in purchasing and supply management: A mixed-methods review of the state-of-the-art in literature and practice. Journal of Purchasing and Supply Management, 30(1), 100896.

Walter, A., Ahsan, K., & Rahman, S. (2025). Application of artificial intelligence in demand planning for supply chains: A systematic literature review. The International Journal of Logistics Management, 36(3), 672–719.

Wellbrock, W., Malinovska, M., & Ludin, D. (2025). Ethical implications and potential opportunities and risks of artificial intelligence in supply chain management. Discover Sustainability, 6, 886.

Yundira, V., & Al Farisi, M. S. (2025). Optimization of Productive Waqf as a Social Investment Instrument from the Perspective of Islamic Economics: Array. International Journal of Sharia Business Management, 4(2), 51-57.

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Published

2026-09-23

Section

Articles