Use Of Artıfıcıal Intellıgence In Enterprıse Resource Plannıng (Erp) Systems

Year 2024, Volume: 8 Issue: 2, 343 - 358

Gizem Oğuz Emine Ağtaş

https://doi.org/10.30692/sisad.1442838

Abstract

Nowadays, where digitalization has become mandatory with the industrial revolution, the impact of the concept of artificial intelligence on human life has reached a level that cannot be ignored and is making progress every day. With this concept, a transition is made to a new industry. This growth of artificial intelligence is revolutionary. Therefore, the use of artificial intelligence in ERP systems, as in many areas, is inevitable. Enterprise resource planning (ERP) systems have recently become an important part of the information technology system. With the age of big data, ERP systems have been exposed to increasing amounts of data in a short time. Processing and controlling this data without error has now become easier with artificial intelligence. In this study, prepared by taking into consideration the concepts of enterprise resource planning (ERP) and artificial intelligence, it is aimed to systematically examine the use of artificial intelligence techniques in ERP systems and to contribute to the literature by revealing the studies carried out in this direction. Within the scope of the study, various articles and books on the use of artificial intelligence in ERP systems were examined based on the existing literature. As a result of the investigations, it has been concluded that businesses have achieved efficiency in areas such as error-free data entry, customer support, sales forecasting and predictive analysis by using artificial intelligence in their ERP systems.

Keywords

Artificial Intelligence, Enterprise Resource Planning (ERP), Information Technologies, Management Information Systems

KURUMSAL KAYNAK PLANLANLAMA (ERP) SİSTEMLERİNDE YAPAY ZEKA KULLANIMI

Abstract

Sanayi devrimi ile birlikte dijitalleşmenin zorunlu bir hâl aldığı günümüzde yapay zeka kavramının insan hayatına etkisi görmezden gelinmeyecek bir boyuta ulaşmış olup her geçen gün ilerleme kaydetmektedir. Bu kavram ile yeni bir endüstriye geçiş yapılmaktadır. Yapay zekanın bu denli büyümesi devrim niteliğindedir. Bu yüzden pek çok alanda olduğu gibi ERP sistemlerinde de yapay zekanın kullanılması kaçınılmaz bir durumdur. Kurumsal kaynak planlama (ERP) sistemleri, son zamanlarda bilgi teknolojileri sisteminin önemli bir parçası haline gelmiştir. Büyük veri çağı ile birlikte ERP sistemleri de kısa bir zamanda artan miktarda veriye maruz kalmıştır. Bu verilerin hatasız işlenebilmesi ve kontrol edilmesi artık yapay zeka ile daha kolay bir hâl almıştır. Kurumsal kaynak planlama (ERP) ve yapay zeka kavramları dikkate alınarak hazırlanan bu çalışmada, yapay zeka tekniklerinin ERP sistemlerinde kullanımını sistematik bir şekilde incelemek ve bu doğrultuda yapılan çalışmaları ortaya koyarak literatüre katkı sağlamak amaçlanmıştır. Çalışma kapsamında ERP sistemlerinde yapay zeka kullanımı ile ilgili çeşitli makale ve kitaplar mevcut literatüre dayandırılarak incelenmiştir. Yapılan incelemeler sonucu, işletmelerin ERP sistemlerinde yapay zeka kullanımıyla, hatasız veri girişi, müşteri desteği, satış tahmini ve tahmine dayalı analiz gibi alanlarda verimliliğe ulaştığı bilgilerine ulaşılmıştır.

Keywords

Yapay Zeka, Kurumsal Kaynak Planlama (ERP), Bilgi Teknolojileri, Yönetim Bilişim Sistemleri

References

• AKBAR, D. M. & HARAHAP, K. (2021). Pengaruh Implementasi Sistem Enterprise Resource Planning (Erp) Terhadap Kualitas Informasi Akuntansi. JAKPI-Jurnal Akuntansi, Keuangan & Perpajakan Indonesia, 9(1), 15.
• AKTÜRK, C. (2021). Artificial Intelligence in Enterprise Resource Planning Systems: A Bibliometric Study. Journal of International Logistics and Trade, 9(2), 69-82.
• ARDITO, L., SCUOTTO, V., DEL GIUDICE, M. & PETRUZZELLI, A. M. (2019). A Bibliometric Analysis of Research on Big Data Analytics For Business and Management. Management Decision, 57(2), 1993-2009.
• AWAD, F.W., MEIDINA, R.D. & AL-ANESI, A.A. (2017). Articifial Intelligence and Digital Assistance Integration into ERP Systems. ERP Research Paper, 1-10.
• AZEVEDO, P. S., ROMÃO, M. & REBELO, E. (2014). Success Factors for Using ERP (Enterprise Resource Planning) Systems to Improve Competitiveness in the Hospitality Industry. Tourism & Management Studies, 10, 165-168. http://www.tmstudies.net/index.php/ectms/article/view/617
• BAHSSAS, D. M., ALBAR, A. M. & HOQUE, M. R. (2015). Enterprise Resource Planning (ERP) Systems: Design, Trends and Deployment. The International Technology Management Review, 5(2), 72-81.
• BIOLCHEVA, P. & MOLHOVA, M. (2022). Integration of AI Supported Risk Management in ERP Implementation. Computer and Information Science, 15(3), 37-46.
• BRINGSJORD, S., GOVINDARAJULU, NS., & SUNDAR, N. (2020). Artificial Intelligence, in, Stanford Encyclopedia of Philosophy. Retrieved from The Stanford Encyclopedia of Philosophy https://plato.stanford.edu/entries/artificial-intelligence/#HistAI
• BRYNJOLFSSON, E. & MCAFEE, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York: W. W. Norton & Company, Inc.
• CORREA, H.L., GIANESI, I.G.N. & CAON, M. (2011). Planejamento, Programação E Contrôle Da Produção: MRP II/ERP - Conceitos, Uso E Implantação Base Para SAP, Oracle Applications E Outros Sof- Twares Integrados De Gestão, 5.Ed. Atlas. São Paulo.
• ENGELBRECHT, A. P. (2007). Computational Intelligence: An Introduction. West Sussex : John Wiley & Sons Online Library.
• GESING, B., PETERSON, S. J. & MICHELSEN, D. (2018). Artificial Intelligence In Logistics: A Collaborative Report By DHL and IBM on Implications and Use Cases for the Logistics Industry. Troisdorf: DHL Customer Solutions & Innovation.
• GOODFELLOW, I., BENGIO, Y., & COURVILLE, A. (2016). Deep Learning. Cambridge : MIT Press.
• GROVER, P., KAR, A. K. & DWIVEDI, Y. K. (2020). Understanding Artificial Intelligence Adoption in Operations Management: Insights From The Review Of Academic Literature and Social Media Discussions. Annals of Operations Research, 308, 1-37. https://doi.org/10.1007/s10479-020-03683-9
• GUPTA, S., QIAN, X., BHUSHAN, B. & LUO, Z. (2018). Role of Cloud Erp and Big Data on Firm Performance: A Dynamic Capability View Theory Perspective. Management Decision, 57(8), 1857-1882.
• HAIDER, L. (2021). Artificial Intelligence in ERP. (Printed Bachelor’s Thesis). Metropolia University.
• HOLSAPPLE, C., SENA, M. & WAGNER, W. (2019). The Perceived Success of ERP Systems for Decision Support. Information Technology and Management, Springer US, 20(1), 1-7.
• HRISCHEV, R., & SHAKEV, N. (2023). Artificial Intelligence In Erp Systems. Engineering Sciences,(1), 3-15. https://doi.org/10.7546/EngSci.LX.23.
• JOURDAN, Z., RAINER, R. K., & MARSHALL, T. E. (2008). Business Intelligence: An Analysis of The Literature. Information Systems Management, 25(2), 121-131.
• JURAFSKY, D., & MARTIN, J. H. (2020). Speech and Language Processing (3rd ed.). Upper Saddle River, New Jersey:Pearson.
• KOKINA, J. D. & THOMAS H. (2017). The Emergence of Artificial Intelligence: How Automation is Changing Auditing. Journal of Emerging Technologies in Accounting, 14 (1), 115-122.
• KÜÇÜKER, M. (2023). Muhasebede Yapay Zekâ Uygulamaları: Chatgpt’nin Muhasebe Sınavı. Fırat Üniversitesi Sosyal Bilimler Dergisi, 33(2), 875-888.
• KUNDURU, A.R. (2023). Effective Usage of Artificial Intelligence in Enterprise Resource Planning Applications. International Journal of Computer Trends and Technology, 71(4), 73-80.
• LUJIC, R., SIMUNOVIC, G., SARIC, T. & MAJDANDZIC, N. (2005). Applying Artificial Intelligence to the Scheduling Problem in the ERP System. 27th Int. Conference on Information Technology Interfaces (ITI), June 20-23, Cavtat, Croatia.
• MADHU, D., JAIN, C. J. N., SEBASTIAN, E., SHAJI, S. & AJAYAKUMAR, A. (2017). A Novel Approach for Medical Assistance Using Trained Chatbot, in, International Conference on Intensive Communication and Computational Technologies (ICICCT), 1(1), 243-246, Coimbatore, India.
• MAHMOOD, F., KHAN, A. Z., & BOKHARI, R. H. (2020). ERP Issues And Challenges: A Research Synthesis. Kybernetes, 49(3), 629-659.
• MARSUDI, A. S., & PAMBUDI, R. (2021). The Effect of Enterprise Resource Planning (ERP) on Performance with Information Technology Capability as Moderating Variable. Journal of Economics, Business, & Accountancy Ventura, 24(1), 1-11.
• MEMİŞ, M.Ü. & TÜM, K. (2011). Sürekli Denetim Süreci ve İç Denetim ile İlişkisi. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 37, 145-162.
• NADIMPALLI, M. (2017). Artificial Intelligence – Consumers and Industry Impact. International Journal of Economics & Management Sciences, 6(4), 1–3.
• NELLI, V. S., PIMENOV, D.Y., MİKOLAJCZYK, T. & MOLDOVAN, L. (2020). Automation of Production Activities of an Industrial Enterprise Based on the ERP System. Procedia Manufacturing, 46, 525-532 https://doi.org/10.1016/j.promfg.2020.03.075
• NEMATI, H. R., STEIGER, D. M., IYER, L. S., & HERSCHEL, R. T. (2002). Knowledge Warehouse: an Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing. Decision Support System, 33, 143-161.
• NORDIN, N. & ADEGOKE, A. (2015). Learning from ERP Implementation: A Case Study of Issues and Challenges in Technology Management. Jurnal Teknologi, 74(1), 57-62.
• ÖZEN, Z., KARTAL, E. & GÜLSEÇEN, S. (2017). Bilgisayar Bilimine Giriş. İstanbul: Papatya Bilim Üniversite Yayıncılığı.
• PUTRA, D. G., RAHAYU, R., & PUTRI, A. (2021). The Influence of Enterprise Resource Planning (ERP) Implementation System on Company Performance Mediated by Organizational Capabilities. Journal of Accounting and Investment, 22(2), 221-241.
• PwC. (2020). Industry 4.0: Building the Digital Enterprise. Retrieved from https://www.pwc.com/gx/en/industries/industry-4.0.html
• RAWAT. C. (2023). Role of ERP Modernization in Digital Transformation: PeopleSoft Insight. International Journal of Computer Trends and Technology. 71(2),61-67.
• REGE, A. (2023). Artificial Intelligence Implementation in SAP. American Journal of Computer Architecture, 10(2), 28-36.
• SELECTHUB (2024). Best ERP Software of 2024, https://www.selecthub.com/c/erp software/#view-contributors SEVİM, A. & BÜLBÜL, S. (2017). Kurumsal Kaynak Planlaması (Enterprise Resource Planning Erp) Sistemlerinin Sürekli Denetimde Yapay Zeka Kullanımı. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 1-12.
• SHI, Z. (2011). Advanced Artificial Intelligence. Hackensack, NJ: World Scientific Pub Co Inc.
• SREE, K., HADADI, M.S., SNEHA, A. & SANDHYA, A. (2022). A Study on AI Based ERP Solution. International Journal of Engineering Research in Computer Science and Engineering (IJERCSE), 9(9), 53-55.
• SVISTUNOV, V. M., LOBACHEV, V. V. & SIMONOVA, M. V. (2020). Staff Responsibility as Efficiency-Driven Factor of ERP-Systems. In Digital Age: Chances, Challenges and Future, 7, 480-486. Springer International Publishing.
• SZELISKI, R. (2010). Computer Vision: Algorithms and Applications. Washington : Springer.
• ÜNVER, M., ALTUNOK, C. (2020). Medikal Endüstride Yapay Zeka ve Uzman Sistemlerin Sürekli İyileştirmeye Etkisi içinde, Proceedings of the 8th International Symposium on Innovative Technologies in Engineering and Science (ISITES2020), 3(1), 482-490. Bursa.
• WENZEL, H., SMIT, D. & SARDESA, S. (2019). A Literature Review on MachineLearning in Supplu Chain Management. W. Kersten, T. Blecker, & C. Ringle (Ed.), in, Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. 27, 413-441. Republi GmbH, Berlin: Proceedings of the Hamburg International Conference of Logistics (HICL). doi: 10.15480/882.2478.