THE USE OF ARTIFICIAL INTELLIGENCE FOR AUTOMATING THE MARINE CREW MANAGEMENT
Abstract
This study presents a comprehensive analysis of the implementation of artificial intelligence (AI) to optimize crew management processes in the maritime industry. The article outlines the inefficiencies of traditional HR practices in shipping companies, including delays in documentation verification, manual classification, and administrative overload. A novel model of an intelligent automation system is introduced, integrating computer vision, machine learning algorithms, and API connections to international registers. The system automates extraction, classification, and real-time validation of seafarers’ documentation. Key improvements include a 70–90% increase in operational efficiency, with error rates reduced by over 90% and verification time shortened from hours to minutes. The paper also describes the patented modular system architecture, which provides multi-level verification and enables secure, scalable document workflows. Its compatibility with cloud infrastructures ensures integration flexibility for international maritime companies. The system processes over 10,000 documents monthly and delivers classification within seconds. The study demonstrates how AI technologies enhance accuracy, transparency, and accountability in HR workflows. By automating routine tasks, it reduces recruiter workload and allows for strategic human decision-making. The solution supports compliance with international standards such as STCW and IMO regulations. Findings suggest this approach enables full-cycle digital crew management, forming the foundation of smart recruiting ecosystems in maritime logistics. These ecosystems use AI-driven tools to solve challenges of operational continuity, regulatory compliance, and global workforce mobility in a digitized shipping environment. The conclusions reinforce the transformative potential of AI in modernizing crew operations, aligning maritime HRM with trends in digital innovation, automation, and secure personnel administration across the global seafaring domain. The article recommends further investigation into hybrid intelligence models that combine algorithmic precision with expert oversight, ensuring both efficiency and contextual accuracy in maritime HR decision-making processes.
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