Artificial Intelligence For Decision Making In The Era Of Big Data Evolution

Abstract

This study systematically examines the transformative role of Artificial Intelligence (AI) in decision-making, focusing on its applications, challenges, and future opportunities. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a total of 100 peer-reviewed articles were analyzed to ensure a rigorous and comprehensive understanding of the subject. The findings highlight AI's ability to optimize decision-making processes through advanced technologies such as machine learning, natural language processing, and predictive analytics, significantly enhancing accuracy, efficiency, and responsiveness across diverse sectors such as healthcare, finance, supply chain management, and public administration. Despite these advancements, the study identifies persistent challenges, including algorithmic bias, data privacy concerns, and the lack of transparency in "black box" AI models, which undermine trust and accountability. Additionally, the review uncovers research gaps, particularly in low-resource settings and emerging markets, where AI's potential remains underutilized due to infrastructural and data limitations. The integration of AI with emerging technologies, such as blockchain, quantum computing, and edge computing, presents promising opportunities to enhance scalability, security, and transparency in decision-making. The study also underscores the importance of interdisciplinary research, particularly at the intersection of AI and social sciences, to better understand human-AI interaction and foster ethical and socially equitable AI adoption. By addressing these challenges and leveraging emerging opportunities, AI can evolve into a transformative tool for informed, inclusive, and responsible decision-making in an increasingly complex world.