Abstract

The rapid evolution of Artificial Intelligence (AI) has significantly transformed the landscape of information retrieval (IR). AI-powered search tools now play a critical role in enhancing the accuracy, relevance, and efficiency of information access across diverse domains. This article explores the integration of AI techniques such as machine learning, natural language processing (NLP), semantic search, and recommendation algorithms in modern search systems. It examines how AIdriven tools understand user intent, personalize search experiences, and manage large volumes of structured and unstructured data. The study also discusses emerging trends like conversational AI, visual search, and AI-based academic search engines. Challenges related to algorithmic bias, transparency, and ethical concerns are considered, alongside future directions for AI-enhanced information retrieval. By highlighting practical applications and critical issues, this article provides valuable insights into how AI is reshaping the search and discovery process in today’s digital era.

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