Evaluating the Impact of Artificial Intelligence Integration on Enterprise Information Systems and Decision-Making Processes
Keywords:
Artificial Intelligence, Enterprise Information Systems, Decision-Making, Machine Learning, Automation, Predictive Analytics, Business IntelligenceAbstract
The integration of Artificial Intelligence (AI) into Enterprise Information Systems (EIS) has transformed how organizations manage data, automate processes, and support decision-making. AI-driven analytics, machine learning models, and intelligent automation enhance operational efficiency and strategic insights by enabling predictive and adaptive functionalities. This paper evaluates the technological, organizational, and managerial effects of AI adoption within EIS, emphasizing decision quality, system performance, and business agility. The study also examines challenges, including data governance, security, integration issues, and workforce readiness. Findings show that AI significantly improves accuracy, responsiveness, and competitiveness in modern enterprises, but requires structured frameworks to ensure sustainable implementation.
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