The impact of artificial intelligence on research efficiency

Abstract

Artificial intelligence (AI) is changing the research landscape through automation, data analysis, and better decision-making in various ways that are of immense help to researchers in conquering obstacles and accelerating their discoveries. From literature search to data analysis, to design experiments and manuscript writing, AI-powered tools using robotics, machine learning (ML), and natural language processing (NLP) go a long way in facilitating easy research. Technology enhances efficiency by summarizing articles, recommending publications, and pointing researchers in the right path. However, challenges such as bias in algorithms, concerns about data privacy, and deficiencies in the infrastructure impede wide-scale application. Training and supporting policies are needed for skill shortages and to surmount resistance to change in order for full utilization of AI in research. The present review has sought to explore how AI has influenced the efficiency of research through an analysis of its uses, advantages, disadvantages, and consequences across many fields. By examining the current tools and making projections on future trends, this study aims at educating academics, policymakers, and institutions on how AI might influence research in a fair and sustainable way.