Ship fires have reached their highest levels in over a decade, with 250 incidents recorded in 2024—a 20% year-on-year increase that's pushing the maritime industry toward unprecedented safety measures. Now, major liner operators representing over 70% of global container capacity have united behind an AI-powered screening program to identify misdeclared dangerous goods before they ignite catastrophic blazes at sea.
The numbers paint a stark picture of maritime risk escalation. According to Allianz's Safety and Shipping Review 2025, there were 250 fire incidents during 2024, up by 20% year-on-year, the highest total for a decade. More alarming is the human cost: misdeclared dangerous goods are reported as responsible for more than a quarter of all cargo-related incidents, with many incidents resulting in crew fatalities and total vessel losses.
The scale of the problem extends beyond individual tragedies. Recent data shows that 11.39% of inspected cargo shipments were found to have deficiencies, up slightly from the IMO's final 2023 figure of 11%. These deficiencies include misdeclared and undeclared dangerous goods, incorrect documentation, and improper packing—all of which can trigger fires that modern vessel systems struggle to contain.
The World Shipping Council's Cargo Safety Program represents the most comprehensive industry response to date, deploying a digital cargo screening tool powered by the National Cargo Bureau's (NCB) technology. It scans millions of bookings in real time using keyword searches, trade pattern recognition and AI-driven algorithms to identify potential risks.
This isn't theoretical screening technology. Hazcheck Detect, launched in September 2020, screens approximately 15 million requests monthly, identifying on average approximately 30,000 suspicious cases. This leads to the prevention of 40-50 high risk containers per week being loaded onto vessels. Major carriers including Maersk, ONE, Hapag Lloyd, and Pacific International Lines have already integrated the system into their operations.
The AI system operates on multiple detection layers. Beyond simple keyword matching, it uses machine learning to identify suspicious trade patterns, unusual commodity descriptions, and last-minute booking changes that often indicate deliberate misdeclaration. When the system flags a potential risk, carriers can order physical inspections before loading, preventing dangerous cargo from ever reaching the vessel.
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The sophistication of this AI deployment extends far beyond basic text scanning. The system processes millions of shipping bookings simultaneously, applying rule-based configuration with approximately 4,500 mis-declared rules and 10,000 undeclared rules available. These rules continuously evolve through machine learning, improving detection accuracy as the system encounters new misdeclaration patterns.
What makes this approach particularly effective is its integration with carrier operations. Search hits are returned from Hazcheck Detect within seconds so that carriers can follow up quickly to ensure that suspicious cargo is not loaded on to the vessels. This real-time capability means dangerous cargo can be stopped during the booking process, not after it's already aboard a vessel carrying thousands of other containers.
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The maritime industry's fire problem reflects the limitations of traditional cargo screening approaches. Physical inspection of even a small percentage of containers creates massive bottlenecks at ports, while manual review of shipping documentation fails to scale with global trade volumes.
60 million packed containers are moved each year, and 10 per cent are declared as dangerous goods. Some ships carry more than 1,000 containers with dangerous goods on any given voyage. The sheer volume makes comprehensive manual screening impossible, creating gaps that determined actors exploit.
The misdeclaration problem often stems from economic incentives. Dangerous goods face higher shipping fees, additional documentation requirements, and special handling protocols. Some shippers deliberately misdeclare cargo to avoid these costs, while others make unintentional errors due to complex regulations and poor compliance training.
Research from the International Maritime Organization indicates that proper dangerous goods declaration and handling can reduce fire risk by up to 60%, making accurate identification critical for maritime safety.
The Cargo Safety Program represents just the beginning of AI's role in maritime safety. Joe Kramek, CEO of the World Shipping Council, noted that the program will continue to evolve, with regular updates to its technology and standards to address new and emerging risks.
Future developments will likely include predictive analytics that identify high-risk trade routes, automated regulatory compliance checking for new dangerous goods classifications, and integration with vessel fire suppression systems for faster response when incidents do occur.
The success of this initiative could accelerate adoption of AI-powered risk management across other supply chain domains. Companies managing complex global freight operations—particularly those dealing with regulated or hazardous materials—should evaluate how similar intelligent screening capabilities could enhance their own risk management protocols.
The maritime industry's AI-powered response to ship fires demonstrates how intelligent systems can address complex safety challenges at global scale. For supply chain leaders, this represents both a model for proactive risk management and an opportunity to evaluate how similar technologies could enhance their own operations.
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