ELNAV.AI, founded by Hrvoje Mihovilović, emphasizes the role of AI in enhancing safety and operational efficiency in the shipping industry. Mihovilović, a seasoned mariner, argues that AI should assist bridge operations rather than audit them, focusing on practical applications that enhance safety without undermining human responsibility.
AI's Role in Shipping Safety
According to Mihovilović, the real value of AI in shipping lies in its ability to support safer watchkeeping, recognize risks earlier, and intervene when fatigue is detected. He stresses the importance of integrating AI into the safety management system with clear limits and traceable outputs. This approach contrasts with using AI for remote monitoring and post-event analysis, which can erode trust and create a blame culture.
Practical Applications Over Autonomy
Mihovilović is not against AI but advocates for its use in areas that improve safety and reduce harm. He believes that AI should not turn seafarers into mere data sources for remote scoring. Instead, AI should reduce operational risks, workload, and improve compliance while preserving professional competence. This perspective challenges the industry's push towards autonomous vessels, which Mihovilović sees as unrealistic for deep-sea operations.
Challenges in AI Implementation
The implementation of AI in shipping faces several challenges. Mihovilović highlights the need for AI systems to be developed by individuals who understand both software and maritime operations. He emphasizes the importance of data governance, cybersecurity, and AI assurance in creating effective AI solutions. The key is to ensure that AI systems make sense in real-world conditions, such as poor visibility or high workload situations.
Future of AI in Shipping
Looking ahead, Mihovilović sees the most important applications of AI in shipping at the intersection of safety, operations, and assurance. Areas like bridge decision support, collision-risk awareness, and fatigue-aware safety support are where AI can make significant contributions. He believes that the long-term winners in the shipping AI race will be those systems that demonstrate safety benefits and withstand scrutiny from various stakeholders.
The future of AI in shipping is not about achieving autonomy but about enhancing human capabilities and ensuring safety, according to Mihovilović.
Conclusion
ELNAV.AI's approach to AI in shipping offers a pragmatic path forward, focusing on enhancing safety and operational efficiency. By prioritizing human-in-the-loop systems and practical applications, the company sets a realistic transition path for the industry. This perspective is crucial for technology decision-makers and digital transformation leaders in the maritime sector, as they navigate the complexities of integrating AI into their operations.
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