Abstract

This study examines the transformative role of artificial intelligence (AI) in academic research, with a focus on hypothesis formulation, research efficiency, accuracy, and ethical standards. AI tools, particularly large language models, enhance hypothesis generation and streamline data analysis, significantly boosting productivity and precision. However, these advances raise ethical concerns, including algorithmic bias, data privacy, and diminished transparency. Using a quantitative approach, this paper investigates the broader impact of AI on scientific inquiry, creativity, and research integrity. By synthesizing current literature and applied examples, it offers critical insights and practical recommendations for the responsible integration of AI across the research lifecycle.

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