<![CDATA[The rapid development of Generative Artificial Intelligence (GenAI) has changed academic learning and writing practices in higher education. For electrical engineering students, scientific writing is a supporting competence because technical knowledge must be communicated through laboratory reports, project documentation, proposals, final projects, and scientific articles. This narrative review examines how GenAI can support scientific writing, identifies benefits relevant to electrical engineering students, analyzes risks, and formulates principles for responsible use. The review incorporated an updated search and verification of recent empirical studies, reviews, and policy guidance, with emphasis on publications from 2023–2026. The evidence indicates that GenAI can assist ideation, brainstorming, outlining, language revision, feedback, and exploratory learning. Engineering studies also report perceived gains in learning efficiency, initiative, creativity, and writing support. However, substantial concerns remain regarding inaccurate outputs, fabricated or erroneous references, overreliance, reduced metacognitive engagement, and academic-integrity risks. In electrical engineering, these risks are amplified because errors in equations, parameters, component specifications, standards, or simulation interpretations can propagate into technical conclusions. This review proposes a Human-Led, AI-Assisted, Evidence-Verified (H-A-E) conceptual model in which students retain responsibility for problem formulation, evidence selection, critical evaluation, technical verification, scientific argumentation, authorship, and final decisions. GenAI is positioned as a cognitive and linguistic assistant, not as a source of scientific evidence or a substitute for engineering judgment.]]>
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