National shipping companies are accelerating their AI transformation (AX), but there are calls for greater collaboration among firms. The Korean Shipping Association recently released a report titled 'Shipping Industry AX Strategy' on September 25, analyzing the AX initiatives of 12 national shipping companies.
The association evaluated the AX progress of shipping companies across 11 categories, including optimal routing, predictive equipment, autonomous navigation, onboard accident prevention, transport demand forecasting, container repositioning, cargo tracking, cargo sales and loading management, cargo safety, smart documentation, and shipper response.
The assessment revealed that only three national shipping companies maintained a level beyond the proof-of-concept stage across their operations. Two companies remained in the review stage for all categories.
When asked about the biggest obstacles to AX in the shipping industry, respondents cited a lack of validation for AI analysis results as the primary issue. Other barriers included insufficient data standardization and reliability.
Additionally, factors such as lack of financial support, insufficient executive commitment, and uncertainty were identified as challenges.
The report suggested focusing on five key areas for AI implementation: optimal routing, smart documentation, predictive equipment, onboard accident prevention, and cargo tracking, recommending a phased approach.
Given the varying sizes and capabilities of shipping companies, the association emphasized the need for differentiated strategies tailored to each company's characteristics rather than a one-size-fits-all AX approach.
A representative from the shipping association stated, "To bridge the gap in AX initiatives among companies, collaborative platform development and outsourcing strategies may serve as viable alternatives to individual investments."
As the shipping industry generates diverse data types related to vessel operations, cargo, and ports, establishing a foundation for standardizing and jointly utilizing information across companies is crucial. Building a shared platform is expected to reduce the initial investment burden for smaller shipping firms.
Meanwhile, the government has begun developing an 'Autonomous Vessel AI Data Platform' to collect and standardize operational data jointly with shipping and shipbuilding companies. HMM, for instance, plans to implement AI-based autonomous navigation solutions from HD Hyundai's subsidiary Avikus on 40 vessels this year, expanding AI applications in the shipping sector.
* This article has been translated by AI.
Copyright ⓒ Aju Press All rights reserved.