INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE MANAGEMENT DECISION-MAKING PROCESS IN THE NEW ERA OF INDUSTRY 4.0

Authors

  • Svetlana Dimitrakieva Department of Industrial Management, Technical University of Varna
  • Marina Marinova-Stoyanova Department of Industrial Management, Technical University of Varna
  • Boris Gramchev Department of Industrial Management, Technical University of Varna

DOI:

https://doi.org/10.17770/etr2025vol4.8451

Keywords:

Artificial Intelligence (AI), Decision-Making, Industry 4.0, Management

Abstract

The integration of AI into management decision-making is transforming businesses in the era of Industry 4.0, driven by technologies like IoT, big data, and cloud computing. This study aims to explore the role of AI in enhancing operational efficiency, reducing costs, and fostering innovation in management practices. The working method involves a review of current literature to assess AI's capabilities, benefits, and associated challenges. AI supports faster, data-driven decisions, improving operational performance and allowing for more strategic, creative work. It aids in risk management, supply chain optimization, and identifying market opportunities. However, AI integration presents challenges, such as implementation complexity, expertise needs, data privacy concerns, and the potential impact on jobs. Ethical issues, including accountability and transparency, are crucial for maintaining trust. Despite these challenges, the study concludes that AI's role in reshaping decision-making offers significant potential for businesses to gain a competitive edge and adapt to changing market dynamics.

 

References

S.Munirathinam, Industry 4.0: Industrial internet of things. Advances in Computers, 117(1), 129-164. https://doi.org/10.1016/bs.adcom.2019.10.010, 2020

E.Brynjolfsson, and А. McAfee,The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Company, 2014

M. Chui, J. Manyika, and M. Miremadi, Where machines could replace humans—and where they can’t (yet). McKinsey Quarterly, 2016

T. H. Davenport & R. Ronanki, Artificial intelligence for the real world. Harvard Business Review, 96(1), 108-116, 2018

A. Agrawal, J. Gans, and A. Goldfarb, Prediction machines: The simple economics of artificial intelligence. Harvard Press, 2018

C., O'Neil, Weapons of math destruction: How big data increases inequality and threatens democracy. New York. Crown Publishing Group, 2016

C. B. Frey and M. A. Osborn, The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 114, 254-280, 2017

G. Westerman, D. Bonnet, &A. McAfee, Leading digital: Turning technology into business transformation. Harvard Press, 2014

H. Mintzberg, Planning on the left side and managing on the right. Harvard Business Review, 54(4), 49-58, 1976

L. P.Vishwakarma, R.K. Singh, R. Mishra and M.Venkatesh, Exploring the motivations behind artificial intelligence adoption for building resilient supply chains: a systematic literature review and future research agenda, Journal of Enterprise Information Management, 37( 4), 1374-1398. https://doi.org/10.1108/JEIM-11-2023-0606, 2024

S. Russell, and P. Norvig, Artificial intelligence: A modern approach. Pearson, 2020

J. Bughin, J. Seong, J. Manyika, M. Chui, & R. Joshi, Notes from the AI frontier—Modeling the Impact of AI on the World Economy. Discussion Paper, McKinsey Global Institute, 2018

T. Choi, S. Wallace &Y. Wang, Big Data Analytics in Operations Management. Production and Operations Management, 27(10), 1868-1883. https://doi.org/10.1111/poms.12838, 2018

J. Dastin, Amazon scraps secret AI recruiting tool that showed bias against women. Reuters, 2018

V. Mayer-Schönberger&K. Cukier, Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt, 2013

P. Grabovy and N. Siniak, Using AI and big data in decision making: A framework across disciplines. E3S Web of Conferences, 535, 2024

K. Schwab, The Fourth Industrial Revolution. New York. Crown Business, 2017

Z. Yi,, X. Cao, Z. Chen & S. Li, Artificial Intelligence in Accounting and Finance: Challenges and Opportunities. IEEE Access, 11, 129100-129123, https://doi.org/10.1109/ACCESS.2023.3333389, 2023

A. Raja Santhi, and P. Muthuswamy, Industry 5.0 or industry 4.0S? Introduction to industry 4.0 and a peek into the prospective industry 5.0 technologies. International Journal on Interactive Design and Manufacturing, 17, 947–979. https://doi.org/10.1007/s12008-023-01217-8, 2023

Z. Jan, F. Ahamed, W. Mayer, N. Patel, G. Grossmann, M. Stumptner, & A. Kuusk, Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities, Expert Systems with Applications, Volume 216. https://doi.org/10.1016/j.eswa.2022.119456, 2023

A. Chymis, Artificial Intelligence in the post-COVID-19 era. Homo Virtualis, 3(2), 55–67. https://doi.org/10.12681/homvir.25449, 2020

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Published

08.06.2025

How to Cite

INTEGRATING ARTIFICIAL INTELLIGENCE INTO THE MANAGEMENT DECISION-MAKING PROCESS IN THE NEW ERA OF INDUSTRY 4.0. (2025). ENVIRONMENT. TECHNOLOGY. RESOURCES. Proceedings of the International Scientific and Practical Conference, 4, 91-98. https://doi.org/10.17770/etr2025vol4.8451