Are natural disasters on the rise? Perhaps, the greater question is: How can the construction industry prepare to build more resilient cities and infrastructure to withstand any threat that comes? And then, also, tangentially: How will AI (artificial intelligence) specifically help build more resilient cities and infrastructure of the future?
First, let’s start with some numbers. Are natural disasters on the rise? Maybe. The National Centers for Environmental Information found there were 27 confirmed weather disaster events—1 drought, 1 flooding, 17 severe storms, 5 tropical cyclones, 1 wildfire, and 2 winter storms—with losses exceeding $1 billion each in the United States in 2024. Looking back, we see the 1980–2024 annual average is 9 events and the annual average for the most recent 5 years (2020–2024) is 23 events.
But, again, the bigger question is what can the construction industry do about this? And the answer will also be building more resilient cities and infrastructure to withstand any natural disaster. That has always been the goal, hasn’t it?
Defining Resilience in Construction
Resilience certainly means different things to different people and different organizations, depending on objectives and perspectives. Some companies may define resilience as the ability to bounce back after a crisis, while others might define resilience as the ability to avoid crisis all together.
The National Academy of Sciences defined resilience as “the ability to prepare and plan for, absorb, recover from and more successfully adapt to adverse events.” Many organizations such as the USGBC (U.S. Green Building Council) have used a similar definition in recent years.
Further, the USGBC (U.S. Green Building Council) suggests resilient structures are better equipped to not just withstand natural disasters but also recover quickly, and that green building and infrastructure certifications can ultimate help ensure a more resilience future for all.
GBRI Online suggests resilient design and building can include design planning, healthy sites, maintaining project sites, and support for community recovery during catastrophic events.
As another example, we see NAHB (National Assn. of Home Builder) suggests voluntary resilient strategies in a home—also known as ‘hardening’ a home—include hazard risk, current local codes, consumer demand, return on investment, and weighing any additional construction costs against the potential costs to repair/rebuild.
AI and Resilience in Construction
How will AI (artificial intelligence) specifically help build more resilient cities and infrastructure of the future? There are perhaps too many opportunities to count. But like anything, it all takes good planning and good data.
One we have already covered came out of Texas A&M University and focuses on retrofitting older buildings, which can help increase resilience against natural disasters such as earthquakes. Agent-based modeling enables researchers to analyze a community’s needs following a seismic event.
With all this data in hand—yes, let me restate again with all this data, a robust simulation is created. This particular study out of Texas A&M University narrows in on the impact retrofitting residential structures would have on community resilience—although there could be similar studies for schools, hospitals, other commercial buildings, and even infrastructure.
Meanwhile, at the NextGen Infrastructure Lab at The University of Mississippi, researchers, professors, and students are considering how different AI algorithms’ abilities can predict potholes, design more durable concrete, and more.
As a specific example, it is using AI to predict how well asphalt pavements with reclaimed asphalt pavement materials could withstand moisture. It found algorithms can predict moisture damage in asphalt mixtures with high accuracy, improving the time-consuming and cost-intensive process of determining the best mixture of reclaimed asphalt pavement in certain environments.
In both of these examples, data is the secret sauce. Data can help build, create, and prepare. Data can also help bounce back and respond when disaster does strike. But our response is only as good as the data we are using.
At the end of the day, we can’t do anything if we don’t have clean data. Everything is going to stem from good data. Resilience is just one example. Stay tuned. Next week we are going to dig a bit deeper into the topic of AI and sustainability in the construction industry. We need our people to look at the data and make good decisions from the data. You might improve productivity with AI, but even greater things can happen when you interpret the data. Be patient, before you terminate your people. Look at the information and think about the future.
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