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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63956
Volume:
10 |
5 |
May 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Management Science (MBA)
D.Y. Patil Institute of Technology, Pimpri, Pune, India
Department of Management Science (MBA)
D.Y. Patil Institute of Technology, Pimpri, Pune, India
Department of Management Science (MBA)
D.Y. Patil Institute of Technology, Pimpri, Pune, India
Department of Management Science (MBA)
D.Y. Patil Institute of Technology, Pimpri, Pune, India
Department of Management Science (MBA)
D.Y. Patil Institute of Technology, Pimpri, Pune, India
Generative Artificial Intelligence (GenAI) has emerged as a transformative technology reshaping enterprise operations and strategic decision-making processes. Modern organizations increasingly adopt AI-powered systems to automate workflows, improve productivity, enhance analytical accuracy, and support real-time business decisions. This research paper examines the strategic impact of Generative Artificial Intelligence on enterprise decision-making efficiency. The study uses both primary and secondary data collected from 10,000 respondents across multiple industries. Statistical tools including percentage analysis, correlation analysis, regression analysis, and hypothesis testing were applied using an SPSS-style analytical approach. The findings indicate that Generative AI significantly enhances enterprise productivity, reduces operational delays, improves strategic planning, and supports intelligent decision-making. The study also highlights implementation challenges such as ethical concerns, data privacy risks, technical complexity, and employee resistance. The research concludes that Generative AI has become a strategic organizational resource capable of improving enterprise competitiveness and business performance.
KEYWORDS
Generative Artificial Intelligence is transforming enterprise operations and strategic decision-making systems. The study demonstrates that AI technologies significantly improve organizational productivity, analytical accuracy, operational speed, and strategic effectiveness. Statistical findings including correlation and regression analysis confirm a strong positive relationship between AI adoption and enterprise decision-making efficiency. Organizations implementing AI systems achieve better workflow automation, improved business intelligence, and competitive advantages. However, enterprises must address challenges related to ethics, governance, privacy, and employee adaptation. Responsible implementation strategies and human supervision are essential for sustainable AI integration. The future of enterprise decision-making will increasingly depend on intelligent systems capable of combining automation, analytics, and human expertise.
1. Brynjolfsson, E., Li, D., & Raymond, L. (2023). Generative AI at Work.McKinsey & Company – The Economic Potential of Generative AI.MIT Sloan Management Review – Generative AI and Productivity.OECD Reports on Artificial Intelligence and Productivity.Harvard Business Review – AI in Enterprise Decision-Making.ResearchGate Publications on Generative AI.Emerald Insight Research Publications.IEEE Research Papers on Artificial Intelligence.Journal of Enterprise Information Management.International Journal of Scientific Research and Engineering Development.
Publication Date
5/25/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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