ARTIFICIAL INTELLIGENCE: A TOOL FOR INFORMATION MANAGEMENT

Artificial Intelligence has emerged as a transformative force reshaping how data is analyzed, information is managed, and decisions are made across economic, industrial, and social sectors. Advances in machine learning, deep learning, and natural language processing have enabled organizations and governments to automate complex tasks, generate predictive insights, and improve efficiency and accuracy. Despite these benefits, the rapid expansion of AI has also raised concerns related to ethics, data quality, transparency, regulation, and workforce implications. The purpose of this research paper is to examine the concept, evolution, applications, and challenges of Artificial Intelligence, with particular emphasis on its role in data analysis and information management. This paper adopts a secondary data approach, drawing on textbooks, peer-reviewed academic journals, government publications, and reports from international organizations such as the World Health Organization and other reputable institutions. Key issues discussed include the historical development of AI, its core technologies, applications in data analytics and information management, economic and social impacts, sectoral relevance, and contemporary challenges such as bias, explainability, privacy, and job displacement. This research also reviews relevant theories and empirical studies to provide a balanced understanding of AI from both technical and socio-economic perspectives. In conclusion, this paper highlights that while Artificial Intelligence offers significant opportunities for innovation, productivity, and informed decision-making, its benefits can only be fully realized through responsible governance, high-quality data practices, and continuous human capacity development. These insights underscore the need for evidence-based policies, ethical frameworks, and further research to support sustainable and inclusive AI adoption.