Harnessing Generative Artificial Intelligence for Academic Research: Capabilities, Challenges, and Ethical Implications

Abstract

This study critically evaluates the role of generative artificial intelligence (GenAI) in reshaping academic research by examining adoption patterns, productivity gains, support for creativity, and the ethical challenges it raises. A qualitative synthesis of 60 scholarly sources published between 2015 and 2025 reveals that GenAI substantially improves efficiency in routine research tasks such as drafting, coding, and literature synthesis, with STEM disciplines reporting up to 50% time savings. Findings further show that GenAI stimulates creativity by offering novel perspectives during idea generation, although its outputs remain constrained by training data and require human interpretation. Despite these advantages, concerns about plagiarism, authorship, and inconsistent disclosure standards emerged as the most frequently cited risks, alongside biases that privilege Western-centric epistemologies. Cross-disciplinary analysis highlights strong STEM adoption, moderate social science use, and cautious humanities uptake due to integrity concerns. Overall, the results underscore GenAI’s dual nature as both an enabler and disruptor, emphasizing the need for institutional policies, disclosure guidelines, and AI literacy programs to balance innovation with scholarly rigor.