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All Journal JUTECH : Journal Education and Technology Data : Journal of Information Systems and Management Digitus : Journal of Computer Science Applications
Setiawan, Adi Wahyu
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Computer Science & IT Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Other

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Journal : Data : Journal of Information Systems and Management

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The Strategic Role of AI in Enhancing MIS Performance and Innovation Setiawan, Adi Wahyu; Cahya, Waskita
Data : Journal of Information Systems and Management Vol. 2 No. 4 (2024): October 2024
Publisher : Indonesian Scientific Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61978/data.v2i4.723

Abstract

The integration of Artificial Intelligence (AI) into Management Information Systems (MIS) has reshaped organizational operations across sectors. This narrative review explores the multidimensional impact of AI on MIS by synthesizing findings from recent peer-reviewed literature. The study aimed to analyze how AI technologies enhance MIS functions, focusing on areas such as process automation, decision support, HR management, corporate learning systems, and export-oriented quality control. Literature was sourced from databases like Scopus and Google Scholar using Boolean search techniques with targeted keywords. Inclusion criteria emphasized relevance, recency, and methodological rigor. Findings indicate that AI and Robotic Process Automation (RPA) optimize operational efficiency, while AI-enhanced decision-making tools offer strategic foresight across industries. In HRMIS, AI facilitates recruitment, performance appraisal, and diversity outcomes, whereas AI-driven learning platforms improve training efficiency and employee engagement. The implementation of AI in quality control and export readiness is linked to higher compliance, predictive analytics, and competitiveness. However, challenges such as algorithmic bias, data inconsistencies, and limited transparency underscore the need for systemic readiness. Theoretical frameworks including the TOE model and RBV elucidate how internal capabilities and environmental contexts shape AI integration. The study concludes that national policies, ethical design, infrastructure development, and cross-sector collaboration are essential for maximizing AI’s potential in MIS, paving the way for responsible and inclusive digital transformation.
Co-Authors cahya, waskita Mahfuzan, Muhammad Saqfan Ratuwulan, Anjelis Saromah, Saromah Yamin, Muhammad Ikrar