The Use of Artificial Intelligence for Decision-Making Process for Strategic Management

Osman Kurter

doi:10.26466/opusjsr.1632110

EN TR

The Use of Artificial Intelligence for Decision-Making Process for Strategic Management

Abstract

Artificial intelligence (AI) is a rapidly developing technology with the potential to create profound changes across various domains, from societal structures to economic systems. This study focuses specifically on the impact of AI on strategic management decision-making processes. The primary aim is to explore how AI can enhance the quality of these processes and contribute to improved organizational performance. A literature review method was employed in the research, through which the theoretical foundations of artificial intelligence, its historical development, and its application areas in decision-making processes were thoroughly examined. The findings indicate that AI accelerates decision-making processes, leading to significant time and cost savings, while also minimizing human error. Decision support systems empowered by AI technologies enable organizations to make more accurate, consistent, and data-driven decisions in strategic management. However, to effectively integrate and benefit from these technologies, organizations must be adequately prepared in terms of both technological infrastructure and organizational culture. In this regard, the study emphasizes that AI is not merely a technical tool, but also a strategic asset that can offer competitive advantages when effectively adopted and utilized

Keywords

Artificial Intelligence , Decision Making , Strategic Management , Application of Artificial Intelligence , Effective Decision Making

Stratejik Yönetimde Karar Alma Sürecinde Yapay Zekanın Kullanımı

Öz

Yapay zeka, günümüzde toplumların işleyişinden ekonomik yapılara kadar pek çok alanda köklü değişimlere yol açma potansiyeline sahip, hızla gelişen bir teknolojidir. Bu çalışma, özellikle yapay zekanın stratejik yönetim karar süreçlerine olan etkisini incelemeye odaklanmaktadır. Temel amaç, yapay zekanın bu süreçlerin kalitesini nasıl artırabileceğini ve organizasyonel performansa nasıl katkı sağlayabileceğini ortaya koymaktır. Araştırmada, literatür taraması yöntemi kullanılmış ve bu bağlamda yapay zekanın teorik altyapısı, tarihsel gelişimi ve karar verme süreçlerindeki uygulama alanları detaylı biçimde ele alınmıştır. Elde edilen bulgular, yapay zekanın karar alma süreçlerini hızlandırarak zaman ve maliyet açısından önemli avantajlar sağladığını, ayrıca insan kaynaklı hataları büyük ölçüde azaltabildiğini ortaya koymaktadır. Yapay zeka destekli karar destek sistemleri sayesinde, stratejik yönetimde daha isabetli, tutarlı ve veriye dayalı kararlar alınması mümkün hale gelmektedir. Ancak bu teknolojilerin etkin bir şekilde kullanılabilmesi için, organizasyonların hem teknolojik altyapı açısından donanımlı olmaları hem de yeniliklere açık bir organizasyonel kültüre sahip olmaları büyük önem taşımaktadır. Bu yönüyle çalışma, yapay zekanın yalnızca teknik bir araç değil, aynı zamanda stratejik bir avantaj unsuru olduğuna dikkat çekmektedir.

Anahtar Kelimeler

Yapay Zeka , Karar Alma , Strategic Yönetim , Yapay Zeka Kullanımı , Etkili Karar Verme

Kaynakça

Abramson, N., Braverman, D., & Sebestyen, G. (1963). Pattern recognition and machine learning. IEEE Transactions on Information Theory, 9(4), 257–261.
Al-Imam, A., Motyka, M. A., & Jędrzejko, M. Z. (2020). Conflicting opinions in connection with digital superintelligence. IAES International Journal of Artificial Intelligence, 9(2), 336-348.
Alenezi, H. S. & Faisal, M. H. (2020). Utilizing crowdsourcing and machine learning in education: Literature review. Education and Information Technologies, 25(4), 2971-2986.
Ashritha, P. & Reddy, P. S. (2023). Impact of artificial intelligence on management decision-making. International Journal of Advances in Business and Management Research (IJABMR), 1(2), 10-18.
Bahrammirzaee, A. (2010). A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems. Neural Computing and Applications, 19(8), 1165-1195.
Barnabè, F. (2011). A “system dynamics‐based Balanced Scorecard” to support strategic decision making: Insights from a case study. International Journal of Productivity and Performance Management, 60(5), 446-473.
Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2019). Supply chain risk management and artificial intelligence: state of the art and future research directions. International journal of production research, 57(7), 2179-2202.
Basak, S., Agrawal, H., Jena, S., Gite, S., Bachute, M., Pradhan, B. & Assiri, M. (2023). Challenges and limitations in speech recognition technology: A critical review of speech signal processing algorithms, tools and systems. CMES-Computer Modeling in Engineering & Sciences, 135(2), 1053-1089.
Bean, R. (2019). Why fear of disruption is driving investment in AI. MIT Sloan Management Review. Boden, M. A. (1984). Impact of artificial intelligence. Futures, 16(1), 60-70.
Borges, A. F., Laurindo, F. J., Spínola, M. M., Gonçalves, R. F., & Mattos, C. A. (2021). The strategic use of artificial intelligence in the digital era: Systematic literature review and future research directions. International journal of information management, 57, 102225.

Bose, B. K. (1994). Expert system, fuzzy logic, and neural network applications in power electronics and motion control. Proceedings of the IEEE, 82(8), 13031323.
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
Boyd, D. & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, Communication and Society, 15(5), 662–679.
Brown, J. A., Ward, A., & Duane, J. N. (2024). Data privacy, ethics and strategic leadership. In Handbook of Research on Strategic Leadership in the Fourth Industrial Revolution, 330-347. Edward Elgar Publishing.
Bruno, Z. (2024). The impact of artificial intelligence on business operations Global Journal of Management and Business Research, 24(1), 1-9.
Burlacu, F. & Luta, G. D. G. (2023). The crucial importance of the European Union AI act as the world's first regulation on artificial intelligence. Journal of Information Systems & Operations Management, 17(2), 59-76
Büyükyılmaz, O. (2024). İşletme yönetim süreçleri ve yapay zekâ. in Gürkan, S. & Aydoğan, D. (Eds.) Işletme ve Yapay Zekâ, 1-18. Ekin Basım Yayın Dağıtım.
Cellan-Jones, R. (2014). Stephen Hawking warns artificial intelligence could end mankind. BBC news, 2(10), 2014.
Chang, W. Y. (2019). A data envelopment analysis on the performance of using artificial intelligence-based environmental management systems in the convention and exhibition industry. Ekoloji Dergisi, 107, 4897.
Chintala, S. (2024). Next-Gen BI: Leveraging AI for competitive advantage. International Journal of Science and Research (IJSR), 13(7), 972-977.
Cockburn, I. M., Henderson, R., & Stern, S. (2019). The impact of artificial intelligence on innovation: An exploratory analysis. (Ed.: A. Agrawal, J. Gans & A. Goldfarb), The Economics of Artificial Intelligence: An Agenda, 115-148. Chicago: The University of Chicago Press.
Craig, P. S., Goldstein, M., Rougier, J. C., & Seheult, A. H. (2001). Bayesian forecasting for complex systems using computer simulators. Journal of the American Statistical Association, 96(454), 717-729.
Cubric, M. (2020). Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study. Technology in Society, 62, 101257.
D’Souza, S., Prema, K. V., & Balaji, S. (2020). Machine learning models for drug–target interactions: current knowledge and future directions. Drug Discovery Today, 25(4), 748-756.
Davenport, T. H. & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116.
Dhaliwal, J. S. & Tung, L. L. (2000). Using group support systems for developing a knowledge-based explanation facility. International Journal of Information Management, 20(2), 131-149.
Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data–evolution, challenges and research agenda. International Journal of Information Management, 48, 63-71.
Duangekanong, S. (2022). Applications of artificial intelligence for strategic management of organization. ABAC ODI Journal Vision. Action. Outcome, 9(2), 202-217.
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719-734.
Edwards, J. S., Duan, Y., & Robins, P. (2000). An analysis of expert systems for business decision making at different levels and in different roles. European Journal of Information Systems, 9(1), 36–46.
Eisenhardt, K. M. (1999). Strategy as strategic decision making. MIT Sloan Management Review, 40(3), 65.
Eisenhardt, K. M. & Zbaracki, M. J. (1992). Strategic decision making. Strategic Management Journal, 13(2), 17-37.
Fjelland, R. (2020). Why general artificial intelligence will not be realized. Humanities and Social Sciences Communications, 7(1), 1-9.
Ford, N. (1989). From information-management to knowledge-management - the role of rule induction and neural net machine learning techniques in knowledge generation. Journal of Information Science, 15(4–5), 299–304.
Foulquier, N., Redou, P., Le Gal, C., Rouvière, B., Pers, J. O., & Saraux, A. (2018). Pathogenesis-based treatments in primary Sjogren's syndrome using artificial intelligence and advanced machine learning techniques: a systematic literature review. Human Vaccines & Immunotherapeutics, 14(11), 2553-2558.
Gladwell, M. (2010). The sure thing.” New Yorker, 85.
Haenlein, M. & Kaplan, A. (2019). A brief history of artificial intelligence: On the past, present, and future of artificial intelligence. California Management Review, 61(4), 5-14.
Harry, A. (2023). Role of AI in Education. Interdiciplinary Journal & Hummanity (INJURITY), 2(3), 259-268.
Haugeland, J. (1989). Artificial intelligence: The very idea. MIT Press.
Ismanov, I., Qayumov, N., Mukhamadjonova, D., & Akhmadaliyev, B. (2024, April). AI and cost management: Strategies for reducing expenses and improving profit margins in business. in 2024 International Conference on Knowledge Engineering and Communication Systems (ICKECS) (1), 1-7. IEEE.
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577-586.
Karnik, A. P., Chhajer, H., & Venkatesh, S. B. (2024). Transforming prosthodontics and oral implantology using robotics and artificial intelligence. Frontiers in Oral Health, 5, 1442100.
Keding, C. (2021). Understanding the interplay of artificial intelligence and strategic management: four decades of research in review. Management Review Quarterly, 71(1), 91-134.
Kedra, J., Radstake, T., Pandit, A., Baraliakos, X., Berenbaum, F., Finckh, A., ..., & Gossec, L. (2019). Current status of use of big data and artificial intelligence in RMDs: a systematic literature review informing EULAR recommendations. Rheumatic Musculoskeletal Diseases (RMD) open, 5(2), 1-8.
Kejriwal, M. (2022). AI in practice and implementation: Issues and costs. In Artificial Intelligence for Industries of the Future: Beyond Facebook, Amazon, Microsoft and Google, 25-45. Cham: Springer International Publishing.
Kersten, F. (1989). Phenomenological method: Theory and practice (Vol. 1). Springer Science & Business Media.
Koch, C. (2016). How the computer beat the go player. Scientific American Mind, 27(4), 20-23.
Kurter, O., Temizkan, V., Yılmaz K., & Yetgin, M. A. (2021). İşletmelerde dijital dönüşüm-Digitaltransformation in businesses. DetayYayıncılık.
Leavy, B. (2020). Marco Iansiti and Karim Lakhani: strategies for the new breed of “AI first” organizations. Strategy & Leadership, 48(3), 11-18.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep Learning. Nature, 521(7553), 436-444.
Lemley, J., Bazrafkan, S., & Corcoran, P. (2017). Deep learning for consumer devices and services: pushing the limits for machine learning, artificial intelligence, and computer vision. IEEE Consumer Electronics Magazine, 6(2), 48-56.
Li, C., Ashraf, S. F., Amin, S., & Safdar, M. N. (2023). Consequence of resistance to change on AI readiness: Mediating–moderating role of task-oriented leadership and high-performance work system in the hospitality sector. sage Open, 13(4), 21582440231217731.
Liang-Pholsena, X. (2020), “Asia’s hotels warming up to automation thanks togrowing social distancing norms, https://skift.com/2020/04/22/asias-hotels-warming-up-to-automation-thanks-to-growing-social-distancing-norms/
McCarthy, J. (2007). From here to human-level AI. Artificial Intelligence, 171(18), 1174-1182.
Michie, D. (1968). “Memo” functions and machine learning. Nature, 218(5136), 19-22.
Micu, A., Capatina, A., Cristea, D. S., Munteanu, D., Micu, A. E., & Sarpe, D. A. (2022). Assessing an on-site customer profiling and hyper-personalization system prototype based on a deep learning approach. Technological Forecasting and Social Change, 174, 121289.
Morocho-Cayamcela, M. E., Lee, H., & Lim, W. (2019). Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions. IEEExplore, 7, 137184-137206.
Müller, V. C. & Bostrom, N. (2016). Future progress in artificial intelligence: A survey of expert opinion. In Vincent C. (Ed), Fundamental issues of artificial intelligence, Springer, 555-572.
Negnevitsky, M. (2008). Computational intelligence applications to crisis management in power systems. International Journal of Automation and Control, 2(2-3), 247-273.
Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104-102117.
Oguntibeju, O. O. (2024). Mitigating artificial intelligence bias in financial systems: A comparative analysis of debiasing techniques. Asian Journal of Research in Computer Science, 17(12), 165-178.
Orgeolet, L., Foulquier, N., Misery, L., Redou, P., Pers, J. O., Devauchelle-Pensec, V., & Saraux, A. (2020). Can artificial intelligence replace manual search for systematic literature? Review on cutaneous manifestations in primary Sjögren’s syndrome. Rheumatology, 59(4), 811-819.
Pancholi, S., Wachs, J. P., & Duerstock, B. S. (2024). Use of artificial intelligence techniques to assist individuals with physical disabilities. Annual Review of Biomedical Engineering, 26.
Perez, J. A., Deligianni, F., Ravi, D. & Yang, G. Z. (2018). Artificial Intelligence and Robotics. arXiv preprint arXiv:1803.10813, 147, 2-44.
Pillai, R. & Sivathanu, B. (2020). Adoption of artificial intelligence (ai) for talent acquisition in it/ites organizations. benchmarking, 27, 2599–629.
Popova, R. & Karadzhov, V. (2023). Artificial intelligence–some ethical issues in the context of state government. in International Applied Social Sciences Congress, 538-556.
Porter, M. E. & Millar, V. E. (1985). How information gives you competitive advantage. Harward Business Review, 63(4), 149-160.
Rawlinson, K. (2015). Microsoft’s Bill Gates insists AI is a threat. BBC News. 29 January 2015.
Rupali, M. & Amit, P. (2017). A review paper on general concepts of Artificial intelligence and machine learning. International Advanced Research Journal in Science, Engineering and Technology, 4(4), 79-82.
Russel, S. J. & Norving, P. (2010). Artificial intelligence. A Modern Approach. (3rd ed.). Pearson.
Sadat, B. (2023). Impact of artificial intelligence on business: An analysis. International Journal of Science and Research, 12(1), 705-709.
Samala, N., Katkam, B. S., Bellamkonda, R. S., & Rodriguez, R. V. (2020). Impact of AI and robotics in the tourism sector: a critical insight. Journal of Tourism Futures, 8(1), 73-87.
Sezer, O. B., Gudelek, M. U., & Ozbayoglu, A. M. (2020). Financial time series forecasting with deep learning: A systematic literature review: 2005–2019. Applied soft computing, 90, 106181.
Sharma, S. (2024). Benefits or concerns of AI: A multistakeholder responsibility. Futures, 103328.
Shiau, W. L., Chen, H., Wang, Z., & Dwivedi, Y. K. (2023). Exploring core knowledge in business intelligence research. Internet Research, 33(3), 1179–1201
Simon, H. A. (1987). Making management decisions: The role of intuition and emotion. Academy of Management Perspectives, 1(1), 57-64.
Simon, H. A. (1979). Rational decision making in business organizations. The American Economic Review, 69(4), 493-513.
Solomonoff, R. J. (1985). The time scale of artificial intelligence: Reflections on social effects. Human Systems Management, 5(2), 149–153.
Spangler, W. E. (1991). The role of artificial intelligence in understanding the strategic decision-making process. IEEE Transactions on Knowledge and Data Engineering, 3(2), 149-159
Srivastava, G. & Bag, S. (2024). "Modern-day marketing concepts based on face recognition and neuro-marketing: a review and future research directions." Benchmarking: An International Journal, 31(2), 410-438.
Stahl, B. C., Andreou, A., Brey, P., Hatzakis, T., Kirichenko, A., Macnish, K., ..., & Wright, D. (2021). Artificial intelligence for human flourishing–Beyond principles for machine learning. Journal of Business Research, 124, 374-388.
Stein, A. L. (2022). Assuming the risks of artificial intelligence. BUL Rev.,102, 979.
Trappl, R. (1986). Impacts of artificial intelligence. North Holland Publishing Co.
Tussyadiah, I. (2020). A review of research into automation in tourism: Launching the Annals of Tourism Research Curated Collection on Artificial Intelligence and Robotics in Tourism. Annals of Tourism Research, 81, 102883.
Valéry, P. (1989). The Outlook for Intelligence:(With a Preface by Francois Valery) (Vol. 10). Princeton University Press.
Vas, P. (1999). Artificial-intelligence-based electrical machines and drives: application of fuzzy, neural, fuzzy-neural, and genetic-algorithm-based techniques (Vol. 45). Oxford University Press.
Vasiljeva, T., Kreituss, I., & Lulle, I. (2021). Artificial intelligence: The attitude of the public and representatives of various industries. Journal of Risk and Financial Management, 14(8), 339-368.
Venkatraman, N. V. (2017). The Digital Matrix: New Rules for Business Transformation Through Technology. Penguin Random House India.
Wang, P. (2019). On defining artificial intelligence. Journal of Artificial General Intelligence, 10(2), 1-37.
Westerman, G., Bonnet, D., & McAfee, A. (2014). The nine elements of digital transformation. MIT Sloan Management Review, 55(3), 1-6.
Wilson, H. J. & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96(4), 114–123.
Wirtz, J., Kunz, W., & Paluch, S. (2021). The service revolution, intelligent automation and service robots. European Business Review, 29(5), 909.
Yeung, K. (2020). Recommendation of the council on artificial intelligence (OECD). International Legal Materials, 59(1), 27-34.
Yigitcanlar, T., Desouza, K. C., Butler, L., & Roozkhosh, F. (2020). Contributions and risks of artificial intelligence (AI) in building smarter cities: Insights from a systematic review of the literature. Energies, 13(6), 1473.
Zekos, G. I., & Zekos, G. I. (2021). AI risk management. economics and law of artificial intelligence: Finance, economic impacts. Risk Management and Governance, 233-288.
Zheng, J. N., Chien, C. F., & Wu, J. Z. (2018). Multi-objective demand fulfillment problem for solar cell industry. Computers & Industrial Engineering, 125, 688-694.
Zhuang, Y. T., Wu, F., Chen, C., & Pan, Y. H. (2017). Challenges and opportunities: From big data to knowledge in AI 2.0. Frontiers of Information Technology & Electronic Engineering, 18(1), 3–14.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Örgütsel Davranış

Bölüm

İnceleme Makalesi

Yazarlar

Osman Kurter ^*
0000-0001-7581-1316
Türkiye

Erken Görünüm Tarihi

25 Mart 2025

Yayımlanma Tarihi

31 Mart 2025

Gönderilme Tarihi

3 Şubat 2025

Kabul Tarihi

24 Mart 2025

Yayımlandığı Sayı

Yıl 1970 Cilt: 22 Sayı: 2

DOI

https://doi.org/10.26466/opusjsr.1632110

IZ

https://izlik.org/JA36CB54MF

APA

Kurter, O. (2025). The Use of Artificial Intelligence for Decision-Making Process for Strategic Management. OPUS Journal of Society Research, 22(2), 195-210. https://doi.org/10.26466/opusjsr.1632110

Cited By

Transformation of School Leadership in the AI Era: Requisite Leadership Roles of Teachers

Journal of Qualitative Research in Education

https://doi.org/10.14689/enad.44.2261

The Use of Artificial Intelligence for Decision-Making Process for Strategic Management

Abstract

Keywords

Stratejik Yönetimde Karar Alma Sürecinde Yapay Zekanın Kullanımı

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Erken Görünüm Tarihi

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster

Cited By

Transformation of School Leadership in the AI Era: Requisite Leadership Roles of Teachers