Artificial intelligence (AI) has rapidly evolved from specialised computational technology into an increasingly accessible component of academic and biomedical research. Contemporary AI systems, including machine-learning applications, generative artificial intelligence and large language models, can support multiple stages of the research lifecycle, from identifying research questions and discovering literature to data analysis, manuscript preparation, peer review and scholarly dissemination. These capabilities offer potential gains in efficiency, accessibility, productivity and communication, but also introduce substantial concerns related to accuracy, hallucination, bias, privacy, intellectual property, reproducibility, research integrity and accountability. This review examines the expanding role of AI across the academic research workflow, with particular attention to health and biomedical research. AI applications are considered according to major stages of research, including research conception, literature discovery, study design, data management, analysis, manuscript preparation, reference management, peer review and dissemination. Evidence indicates that AI can augment repetitive and language-intensive tasks, but performance remains variable and human verification is essential. Recent evaluations have demonstrated limitations in AI-generated references, literature retrieval and interpretation, while emerging guidance from international organisations and editorial bodies emphasises transparency, human oversight, confidentiality and responsible governance. The appropriate role of AI is therefore better conceptualised as research augmentation rather than replacement of scholarly judgement. Responsible integration requires AI literacy, verification procedures, transparent disclosure, protection of confidential information and clearly defined human accountability. Future research should establish validated frameworks for evaluating AI-assisted research quality, reproducibility, equity and ethical performance.

Keywords: Artificial Intelligence, Generative Artificial Intelligence, Biomedical Research, Research, Scholarly Communication.