Optimizing Regulated Content Creation with Generative AI: A Mixed-Methods Study of AviationGPT in MRO Marketing

Abstract

Aviation maintenance, repair, and overhaul (MRO) content marketing requires technical precision and regulatory compliance, often sacrificing efficiency. This study evaluates AviationGPT in revolutionizing MRO content creation. Employing a mixed-methods approach, ANOVA, Tukey’s HSD, and expert evaluations, we compared AI-generated, AI-enhanced, and human-generated content across 180 samples. Results demonstrate that AI-initiated content refined by human expertise significantly outperforms fully human-driven and human-initiated, AI-refined methods in consistency, scalability, and engagement. A proposed human-AI collaboration framework integrates AI’s automation with human oversight across ideation, writing, distribution, and continuous improvement, ensuring compliant, high-impact content. This research provides actionable insights for regulated industries, advancing operational efficiency while upholding ethical governance and strategic alignment, in support of the United Nations Sustainable Development Goals (SDGs).
Keywords: AviationGPT, Aviation MRO, Content Marketing, Generative AI.