Natural disasters have caused nearly 200 billion dollars in global infrastructure losses every year for the past 15 years. A recent Deloitte report warns that this figure could almost double by 2050.
The good news is that advances in AI, particularly in predictive resilience technology, could prevent up to 15 percent of these losses. That translates to as much as 70 billion dollars saved by mid-century. For those committed to global resilience, this is a pivotal moment to rethink how we prepare for and respond to disasters.
Why AI Is Transforming Resilience Planning
AI is no longer just a buzzword. It is becoming a core capability for cities, utilities, and infrastructure operators to plan, respond, and recover from crises. Deloitte’s research points to three critical stages where AI can deliver measurable impact:
- Planning – using digital twins to identify and understand system vulnerabilities
- Response – applying predictive analytics to guide rapid, preventive action
- Recovery – accelerating restoration through data-driven decision-making
Many regions still face infrastructure gaps, limited funding, fragmented governance, and siloed data systems. Security concerns also remain a major challenge. That is why collaboration is essential. At the EIS Council, our mission is to bring together governments, utilities, academia, and the private sector to close these gaps and strengthen resilience worldwide.
As Jennifer Steinmann, Deloitte Global Sustainability Business Leader, explains, “Investing in AI can help deliver less frequent or shorter power outages, faster system recovery after storms, or fewer damaged or non-usable roads and bridges.”
The report also warns that climate change is likely to increase both the frequency and intensity of severe weather events, making the case for predictive resilience even stronger. Storms such as tropical cyclones, tornadoes, thunderstorms, hailstorms, and blizzards already account for the largest share of infrastructure losses because of their high frequency, wide reach, and growing intensity.
Predictive Resilience in Action
One of the most innovative tools in predictive resilience today is Ginom, a real-time, multi-sector resilience simulation platform developed with the support of the EIS Council. Ginom models interconnected infrastructure, supply chains, and resources, providing a realistic, evolving picture of how a crisis might unfold across multiple sectors.
What sets Ginom apart is that it does not require every organization to share sensitive data into a central database. Instead, it links existing sector-specific simulations into one secure, coordinated framework. This allows operators to:
- See the broader interdependencies between systems
- Understand cross-sector impacts before they escalate
- Receive prioritized, actionable recommendations during a crisis
Ginom’s agent-based modeling, resource flow tracking, and multi-day crisis simulations give decision-makers the situational awareness they need when time is short and stakes are high. It is already being used to model complex scenarios such as large-scale power outages, fuel shortages, water system disruptions, and extreme weather events.
By integrating Ginom into preparedness planning, organizations can test “what if” scenarios in a safe environment, refine their response strategies, and coordinate more effectively across sectors.
How to Move Forward with Predictive Resilience
To maximize the value of AI and predictive resilience technologies, organizations can:
- Start small – pilot projects focused on specific risks, such as storm response or grid protection
- Integrate existing models – connect them into shared platforms like Ginom for a comprehensive, cross-sector view
- Secure funding – explore innovation programs, resilience bonds, and insurer-backed incentives
- Share best practices – exchange lessons learned to scale what works
Predictive resilience is no longer optional. It is becoming the backbone of how we prepare, respond, and recover from disasters. By combining AI-powered planning tools with innovative platforms like Ginom and fostering collaboration across sectors, we can significantly reduce the damage and disruption caused by tomorrow’s disasters.
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