Impact of Artificial Intelligence on Business Decision-Making in the Digital Era

International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, SI1 (2026), pp. 300–308
Proceedings of Selected Papers from the
National Conference on Emerging Trends in Commerce and Management
NCETCM-2K26
2026-03-30 to 2026-03-31
Vijayawada, Andhra Pradesh, India
Organized by Andhra Loyola College, Vijayawada, India
eISSN: 3107-9075

This work is licensed under a Creative Commons Attribution 4.0 International License .

Impact of Artificial Intelligence on Business Decision-Making in the Digital Era

1Vijay Kolluri, 1Vasu Dammati, 2T Chaitanya Lakshmi

1Assistant Professor, Department of Business Administration, P.B. Siddhartha College of Arts and Science, Vijayawada, India
2Independent researcher, Vijayawada. India

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in the digital economy, significantly influencing business decision-making processes across industries. With the exponential growth of data and advancements in machine learning technologies, organizations increasingly rely on AI-driven tools to enhance the accuracy, speed, and efficiency of managerial decisions. This study examines the role of AI in improving decision-making processes, analyses its impact on organizational performance, and evaluates its applications across key business functions such as marketing, finance, operations, and human resource management. The research adopts a conceptual research design and is based on secondary data collected from academic journals, books, industry reports, and credible online sources. The findings suggest that AI-driven decision-making improves organizational efficiency, reduces uncertainty, and enhances competitive advantage in the digital era. The study also highlights major challenges in AI adoption and provides recommendations for effective AI implementation in organizations.

Keywords: Artificial Intelligence, Decision Support Systems, Business Analytics, Digital Transformation, Data-Driven Decision Making.

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DOI: 10.66710/ijersem.v2si1.38

Open Access • Peer Reviewed Article

References

  1. N. Soni, E. K. Sharma, N. Singh, and A. Kapoor, “Artificial Intelligence in Business: From Research and Innovation to Market Deployment,” Procedia Computer Science, vol. 167, pp. 2200–2210, Jan. 2020. https://doi.org/10.1016/j.procs.2020.03.272
  2. H. Benbya, T. H. Davenport, and S. Pachidi, “Artificial Intelligence in Organizations: Current State and Future Opportunities,” SSRN Electronic Journal, Jan. 2020. https://doi.org/10.2139/ssrn.3741983
  3. M. H. Jarrahi, “Artificial Intelligence and the Future of Work: Human-AI Symbiosis in Organizational Decision Making,” Business Horizons, vol. 61, no. 4, pp. 577–586, Apr. 2018. https://doi.org/10.1016/j.bushor.2018.03.007
  4. Y. R. Shrestha, S. M. Ben-Menahem, and G. von Krogh, “Organizational Decision-Making Structures in the Age of Artificial Intelligence,” California Management Review, vol. 61, no. 4, pp. 66–83, Jul. 2019. https://doi.org/10.1177/0008125619862257
  5. A. Kuzior, M. Sira, and P. Brożek, “Effect of Artificial Intelligence on the Economy,” Scientific Papers of Silesian University of Technology Organization and Management Series, vol. 2023, no. 176, Jan. 2023. https://doi.org/10.29119/1641-3466.2023.176.19
  6. J. Cao, “Intelligent Decision-Making in Business Management: Integrating Artificial Intelligence and Big Data Analytics for Strategic Optimization in Enterprise Operations,” Sustainable Computing: Informatics and Systems, p. 101382, May 2026. https://doi.org/10.1016/j.suscom.2026.101382
  7. T. Lindner, J. Puck, and H. Puhr, “Artificial Intelligence in International Business: IB Theory under Augmented Decision-Making,” Journal of World Business, vol. 60, no. 6, p. 101676, Sep. 2025. https://doi.org/10.1016/j.jwb.2025.101676
  8. L. Sailer, “Explainable Artificial Intelligence in Finance: Mapping Business Problems and Technological Solutions,” Finance Research Open, p. 100128, May 2026. https://doi.org/10.1016/j.finr.2026.100128
  9. Y. Wang, Z. Wu, and J. Zhang, “Blind Imitation or Rational Decision-Making? The Impact of Generative Artificial Intelligence on Corporate Investment Herd Behavior,” International Review of Economics & Finance, vol. 107, p. 105139, Mar. 2026. https://doi.org/10.1016/j.iref.2026.105139
  10. F. Binsar, I. Wahyudi, G. D. P. Atmoko, F. Nurdin, and T. N. Santoso, “Optimizing Business Competitiveness through Artificial Intelligence: A Framework for Digital Innovation and Operational Efficiency,” Advances in Business and Management Research, vol. 1, p. 100002, Feb. 2026. https://doi.org/10.1016/j.abmr.2026.100002
  11. S. Eti, S. Yüksel, H. Dinçer, K. Köklü, and A. N. Çırak, “Addressing Energy Efficiency Challenges in Artificial Intelligence Hardware Using a Novel Behavioral Fuzzy Decision-Making Approach,” Energy Conversion and Management X, vol. 30, p. 101884, Apr. 2026. https://doi.org/10.1016/j.ecmx.2026.101884
  12. Poli Rajitha and V. Mouneswari, “A Study on Demographic Influence on Employee Performance in Select IT Companies Hyderabad,” International Journal of Emerging Research in Science Engineering and Management, vol. 2, no. si1, pp. 293–299, May 2026. https://doi.org/10.66710/ijersem.v2si1.37

This article is part of Volume 2, Special Issue 1 (May 2026)

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2026-05-19