Objective: Our study aimed to compare the efficacy of artificial intelligence (AI)-based immersive training with human-led workshops to improve the English language skills of non-English early career researchers (NEECRs) in a Nigerian public university. Methods: Our study employed a randomized pretest/posttest control group design. A total of 124 NEECRs in Federal University Oye-Ekiti, Nigeria, who met the eligibility criteria participated in the study. NEECR participants were randomly assigned to 8 weeks of self-directed AI immersion (n = 62) or human-led workshops (n = 62). A 56-item questionnaire collected data pretreatment, posttreatment, and at a 3-month follow-up. Repeated-measures ANOVA analyzed differences between and within the groups over time. Effect sizes were calculated using partial eta squared ([partial eta-squared]). Prior to analysis, Mauchly's test of sphericity was conducted to test the assumption of sphericity, yielding a nonsignificant result (W = 0.950, p = 0.247), indicating the assumption was not violated. Results: No initial group differences were found on pretest measures (all p > 0.05). At posttest, the AI group significantly outperformed the human-led group on all skills (p < 0.001, large effect sizes). For example, vocabulary scores were 22.1 for the AI group versus 20.4 for the human-led group. Similar significant results favoring the AI group were seen at the 3-month follow-up. Time-by-group interactions showed greater gains from AI workshops. Conclusions: AI-immersive instruction was found to be more effective in developing English proficiency in early career researchers compared with traditional human-led methods across all the domains measured. The findings suggested AI could help promote international scholars' career advancement. Implications: Our study implicated the strategic use of AI to develop NEECRs' English abilities. Institutions should consider incorporating AI-assisted language training to support internationalization goals and researcher career success in the English-dominated landscape of international scholarship. Policymakers could view the strategic incorporation of AI for language development favorably as a means to strengthen international competitiveness among researchers.