A Systematic Review of Artificial Intelligence Enabled Data Driven Decision Making in Management and IT
DOI:
https://doi.org/10.63682/jns.v13i1.9260Keywords:
Artificial Intelligence, Data-Driven Decision Making, Management, Information TechnologyAbstract
The integration of Artificial Intelligence (AI) into management and information technology (IT) has transformed organizational decision-making by moving from intuition-driven approaches to data-driven strategies. This systematic review synthesizes literature published between 2020 and 2023, examining how AI-enabled tools such as machine learning, predictive analytics, and natural language processing enhance decision accuracy, efficiency, and adaptability. In management, AI supports strategic planning, resource optimization, and performance evaluation, while in IT, it strengthens automation, cybersecurity, and real-time operational responsiveness. Research contributions are categorized into areas such as AI-driven decision support systems, integration with enterprise IT infrastructures, and issues of interpretability, transparency, and data governance. Although evidence suggests AI improves accuracy, speed, and scalability, significant challenges remain, including algorithmic bias, ethical concerns, and limited alignment between technical advancements and managerial expertise. To address these gaps, the objectives of this review are: (1) to systematically analyze recent advancements in artificial intelligence-enabled data-driven decision making and their applications in management and IT, and (2) to identify key challenges and future opportunities for integrating AI into organizational decision-making processes for sustainable and ethical growth. By fulfilling these objectives, the study provides a consolidated framework that highlights the synergy between management and IT through AI-enabled decision making, offering valuable insights for researchers, practitioners, and policymakers seeking to leverage AI responsibly to achieve competitive advantage, ethical practices, and sustainable organizational development.
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