A Comprehensive Survey of AI-Driven Research Support Systems

Artificial Intelligence (AI) is transforming the research ecosystem by enhancing efficiency, accuracy, and innovation across the entire research lifecycle. This paper reviews the role of AI in accelerating scientific research, from problem identification and literature analysis to experimental design, data analysis, manuscript writing, and ethical compliance. AI-driven tools enable researchers to identify knowledge gaps, optimize experiments, automate data processing, and generate predictive insights from complex and high-dimensional datasets. In addition, AI supports scholarly communication by improving manuscript quality, reference management, plagiarism detection, and journal selection, while also strengthening research ethics through transparency, integrity checks, and responsible data handling. The integration of AI with traditional scientific methods represents a paradigm shift toward data-driven and adaptive research practices, particularly in fields such as physics, materials science, energy, and healthcare. This review highlights how responsible and human-supervised use of AI can significantly enhance research productivity, reliability, and impact.