Writing a research paper with artificial intelligence: a step-by-step guide for junior researchers

Abstract

Early-career researchers often have a sound idea yet struggle to turn it into a publishable manuscript that reviewers can trace and evaluate. This paper synthesizes practical guidance on structuring and drafting research articles using the introduction-methods-results-and-discussion (IMRaD) convention, while addressing emerging concerns about the responsible use of generative artificial intelligence (AI) in academic writing. A documentary narrative synthesis was conducted using 36 high-authority sources, including writing guides, guidance from journal editors, publisher and ethics policies, and recent empirical studies on AI-assisted writing. Recommendations were coded using an explicit IMRaD-aligned codebook and then consolidated into a step-by-step workflow from question formulation to submission checks. The synthesis indicates that treating IMRaD as a traceability checklist improves alignment between research questions, methods, results, and claims, and that iterative revision is more effective than one-pass drafting. AI support is most defensible when limited to language and process assistance, combined with disclosure, reference verification, and full human accountability for all content. The paper concludes with an actionable checklist and a visual ‘traceability map’ that can be adapted for research training and supervision.