The Role of Artificial Intelligence in Enhancing Decision-Making Processes in Modern Organizations

Giulia Esposito

Authors

Giulia Esposito Università degli Studi di Milano

Keywords:

Artificial Intelligence (AI), Decision-making processes, Organizational strategy, AI-driven insights, Operational efficiency, AI in business

Abstract

The integration of Artificial Intelligence (AI) into organizational decision-making processes is revolutionizing the way modern businesses operate. This paper examines the role of AI in enhancing the efficiency, accuracy, and strategic depth of decision-making across various industries. By leveraging technologies such as machine learning, natural language processing, and predictive analytics, organizations can process vast amounts of data, identify patterns, and make informed decisions with unprecedented speed and precision. The study draws on multiple case studies to demonstrate how AI-driven decision-making not only improves operational efficiency but also fosters innovation and competitive advantage. Moreover, it discusses the challenges associated with AI adoption, including data privacy concerns, ethical considerations, and the need for skilled personnel. The findings underscore the transformative potential of AI in reshaping decision-making paradigms, ultimately enabling organizations to navigate complex environments and achieve sustainable growth. This research contributes to the growing body of knowledge on AI applications in business and provides actionable insights for managers seeking to harness AI's capabilities in their decision-making processes.

References

Bessen, J. E. (2019). AI and jobs: The role of demand. NBER Working Paper No. 24235. National Bureau of Economic Research.

Brynjolfsson, E., & McAfee, A. (2017). The business of artificial intelligence: What it can—and cannot—do for your organization. Harvard Business Review.

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

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

Frank, M. R., Autor, D., Bessen, J. E., Brynjolfsson, E., & Cebrian, M. (2019). Toward understanding the impact of artificial intelligence on labor. Proceedings of the National Academy of Sciences, 116(14), 6531–6539.

Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155–172.

Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586.

Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389–399.

Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60.

Ransbotham, S., Khodabandeh, S., Kiron, D., & Kiron, D. (2018). Artificial intelligence in business gets real. MIT Sloan Management Review, 60(1), 1–17.

Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66–83.

Topol, E. (2019). Deep medicine: How artificial intelligence can make healthcare human again. Basic Books.

Wilson, H. J., & Daugherty, P. R. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96(4), 114–123.

Brock, J. K.-U., & von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California Management Review, 61(4), 110–134.