The tech that could stop a catastrophe

In control rooms, camera towers and server farms across the globe, artificial intelligence is reshaping the disaster response frontline.

This article is sponsored by FM

Artificial intelligence is rapidly transforming disaster preparedness, offering unprecedented capabilities to detect, predict, and mitigate crises across the globe. From the bushlands of Tasmania to the typhoon-prone coasts of Taiwan and the vast rail networks of the United States, AI is increasingly being harnessed in innovative ways to enhance safety and resilience.

AI-enhanced bushfire detection

In Tasmania, the integration of AI into bushfire detection marks a significant advancement in environmental monitoring. Forico, the state's largest private forest manager, has deployed AI-powered cameras developed by Pano AI across its 173,000 hectares of managed land. 

These ultra-high-definition, 360-degree panoramic cameras, combined with satellite technology and advanced AI algorithms, enable the early detection of fire, allowing for a swift response. 

The system is helping reduce the risk of catastrophic bushfires, and lessen the increase in fire affected areas – which have grown by around 48,000 hectares per year for the past three years. It is also helping safeguard natural resources and protect critical infrastructure projects.

AI-driven typhoon forecasting

Taiwan, frequently impacted by typhoons, is now using AI to improve storm forecast accuracy. The Central Weather Administration (CWA) has collaborated with tech companies like NVIDIA to implement AI models such as CorrDiff. 

During Typhoon Koinu last year, the CWA deployed advanced AI models that successfully forecast the storm’s trajectory five days in advance. Three days before the typhoon made landfall, the CWA issued a heavy rainfall disaster warning, triggering large-scale evacuations in high-risk areas. 

Local governments were able to implement early warning systems and move vulnerable communities to safety.

The case highlights how AI is strengthening disaster planning by enabling earlier forecasting and how it’s turning time into a valuable emergency management resource.

Preventing train derailments

In the United States, the railway industry is leveraging AI to prevent train derailments, a persistent safety concern. 

Companies like Norfolk Southern have installed automated inspection portals equipped with high-speed cameras and AI software along their tracks. These systems analyse real-time data to detect defects on moving trains, allowing for immediate corrective actions.

The initiative aims to enhance safety by identifying potential issues before they lead to accidents, reflecting a proactive approach to infrastructure maintenance and disaster prevention.

Intercepting disaster

While AI is making a huge difference on the ground, helping reduce the impacts of disasters or even prevent them in the first place, it is also making a big difference in industry.

A 2021 report by Deloitte found natural disasters alone cost the Australian economy $38 billion a year, and that figure is expected to rise dramatically in coming years. Other disasters, such as accidents add much more to this cost.

Which is why insurance companies are leaning into the power of AI to help reduce the cost of these disasters.At commercial property insurer FM, AI is working in conjunction with people to reshape how complex risks are understood and mitigated.

The technology is helping turn the company’s centuries of engineering insight into a cutting-edge tool for disaster prevention – especially in heavy industries critical to Australia’s economy.

FM Senior Vice President for Asia Pacific James Thompson said AI is a common-sense next step for the company.

FM Senior Vice President for Asia Pacific James Thompson

“AI is simply the next evolution in bringing science and engineering to risk. ,  Our philosophy has always been to learn from prior incidents and prevent their recurrence.”

The insurer leverages data from over 60,000 facility visits annually, along with $4.6–6.1 billion in yearly claims data, to train AI models that predict which pieces of equipment are most likely to fail. This approach, called “equipment pre-disposed”, lets engineers target failure points in sectors like mining, power generation and chemical manufacturing before disaster strikes.

“Artificial intelligence helps us interrogate the combination of facility data and loss data to find the key patterns that lead to loss events,”  Mr Thompson said. “It enables us to turn noise into insight.”

But he warned against blind reliance on algorithms. “We’re not ready for self-driving risk management. Hands still on the wheel and eyes on the road, please.”

Global implications and the path forward

The adoption of AI in disaster management signifies a shift in how societies anticipate and respond to emergencies. By enabling early detection and more precise forecasting, AI technologies contribute to more effective resource allocation, timely evacuations, and overall risk reduction. 

However, the integration of AI also necessitates considerations regarding data privacy, ethical use, and the need for human oversight to interpret AI-generated insights accurately.

As climate change continues to exacerbate the frequency and severity of natural disasters, the role of AI in disaster preparedness and response is likely to become increasingly vital. 

Continued investment in AI research and infrastructure, coupled with international collaboration, will be essential in harnessing the full potential of AI to safeguard communities and build resilience against future crises.

FM works to understand individual businesses and their specific risk exposures. For a detailed consultation, evaluation and risk report, contact FM today by visiting fm.com.