Rahman, Md Shihab (2026) AI-Driven MIS Evolution: A Review on Optimizing Operational Efficiency, Consumer Engagement, and Socio-Economic Sustainability. American Journal of Technology Advancement, 3 (7). ISSN 2997-9382

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Abstract

Artificial Intelligence (AI) has revolutionized the role of Management Information Systems (MIS) by bringing in a new era of intelligent, predictive, and automated decision-making support to help organizations make more informed choices. This review explores how MIS has been evolving to become more AI-powered and how this development is helping to streamline business operations, enhance customer interactions, and drive positive social and economic outcomes in various industries. It considers the evolution of MIS, the incorporation of AI technologies like machine learning, deep learning, natural language processing, and predictive analytics, and the transformation of enterprise decision-making.  It also discusses the architecture of AI-driven MIS, optimization dimensions, methods to evaluate its performance, strategies for implementing it, its practical applications, and the governance requirements. The review points out the benefits of AI in ERP, CRM, DSS, and business intelligence systems, such as better process automation, resource management, customer personalization, and organizational responsiveness. AI-powered information systems are currently playing a significant role in various sectors such as manufacturing, healthcare, finance, government, retail, and smart city management, all of which rely on the power of AI to aid in the decision-making process and operational efficiency. The study further explores critical issues that arise with the use of AI, such as privacy, cybersecurity, explainability, adapting the workforce, ethical governance, and sustainability. In the broader context, AI-driven MIS is a paradigm shift that combines intelligent technologies with enterprise information systems to enhance organizational effectiveness, foster customer relations, and drive long-term socio-economic sustainability.

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence, Management Information Systems, Decision Support Systems, Operational Efficiency, Socio-Economic Sustainability
Subjects:	H Social Sciences
Depositing User:	admin eprints
Date Deposited:	01 Aug 2026 09:11
Last Modified:	01 Aug 2026 09:11
URI:	http://eprints.umsida.ac.id/id/eprint/16873

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