The development of modern information systems requires more intelligent, adaptive, and efficient data processing capabilities due to the increasing complexity and volume of data. Artificial Intelligence (AI) has emerged as a strategic solution to enhance the ability of information systems to perform analysis, prediction, and data-driven decision support. This study aims to examine the integration of artificial intelligence in the development of modern information systems from the perspective of electrical engineering and systems engineering. The research adopts an applied research approach using a systems engineering methodology, which includes problem identification, literature review, system architecture design, simulational implementation, and performance testing and evaluation. The results indicate that modular integration of artificial intelligence significantly improves data processing efficiency, analytical accuracy, and system adaptability to changing data patterns. AI-based information systems demonstrate superior performance compared to conventional systems, particularly in supporting proactive and predictive decision-making processes. Furthermore, AI integration contributes positively to computational resource efficiency, which is a critical aspect of sustainable information system development. However, the findings also highlight that data quality and proper system architecture design are decisive factors for successful AI implementation. This research provides both conceptual and technical contributions that can serve as a reference for the development of modern AI-driven information systems and as a foundation for future studies in this field.
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