<![CDATA[The shipping industry relies heavily on efficient crewing management to ensure safe vessel operations and compliance with national and international regulations. In Indonesia, crewing management faces persistent challenges, including complex documentation procedures, manual data processing, high administrative workloads, and limited integration between human resource systems and operational platforms. With the rapid expansion of artificial intelligence (AI) technologies, maritime companies increasingly explore AI-based solutions to optimize decision-making, automate routine processes, and enhance overall crew management performance. This study conducts a systematic literature review to analyze the potential, limitations, and implementation models of AI within the context of crewing management systems (CMS). The result shows that AI significantly improves crew scheduling accuracy, reduces administrative workload by up to 40%, enhances regulatory compliance monitoring, and supports predictive analytics for crew performance and turnover. The study concludes that AI-enabled CMS could transform Indonesia’s shipping operations, although challenges remain in terms of digital readiness, data quality, cybersecurity, and regulatory frameworks. Recommendations are provided to support Indonesian shipping companies in adopting AI-driven crewing management solutions]]>
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