How Artificial Intelligence Technology and Data Can Increase Resilience in the New Pandemic Era 

If there’s a common thread over the past year and a half, it’s dramatic change: a global pandemic amidst a politically charged and socially divisive environment, civil unrest, extreme temperatures and record-breaking weather disasters.

These disasters have all driven immense transformation. From the collaboration required between state and health care to manage COVID-19 outbreaks and vaccine appointments to remote working, adopting new ways to support customers and operating brick-and-mortar processes in a digital environment, technology has been interwoven into the response and management of crises.

While we have certainly learned a lot in the last 18 months, we must also look ahead to how these changes will shape our future. What role will technology play in helping us mitigate challenges in the new era of the pandemic? Without question, business and communities have made a dramatic shift toward investing in big data and artificial intelligence. What will be important is to understand how big data and AI will keep our infrastructure ahead of disasters and, ultimately, more resilient in dealing with future events.  

The events of 2020 exposed several vulnerabilities in public and private sector systems and infrastructure, including cybersecurity postures, workforce mobility and supply chain systems. Cybercriminals took advantage of massive disruption in 2020, exploiting many organizations’ shift to remote work. As of September 2020, 63% of government employees were working full time in a remote environment. And acute examples of supply chain disruptions have occupied headlines for months, from shortages in toilet paper, canned goods and cleaning supplies to fuel shortages due to the Colonial Pipeline ransomware attack. According to an Ernst & Young survey of 200 senior supply chain executives, only 2% said they were fully prepared for the pandemic. 

How AI and Data Can Help

The pandemic exposed levels of fragility that varied across different parts of the country in response to several challenges. There are seemingly endless risks that government organizations can face that could directly impact resilience strategies and, often, an organization's ability to fulfill its charter.

As the number of threats facing agencies increases, so should the speed with which they work to identify and act upon threats. This growing demand for risk intelligence technology is driving the latest innovations in the field. 

During the pandemic, our lives were bolstered by digital and virtual activity. While we can’t stop crises from happening, we can find ways to use data to anticipate impact and enable deployment of appropriate resources to help with recovery. This starts with putting the right infrastructure in place. Agencies can establish a data capture process, using AI, to instantly gather and monitor threats facing them, such as an evolving hurricane or snowstorm, and correlate it to entities such as people, places and property, including highly populated areas, major power lines, neighborhoods, schools and hospitals. Armed with this data, public sector organizations such as the Federal Emergency Management Agency could work closely with the private sector to predict needs, such as lumber to rebuild, equipment to remove trees or fix power lines, and even services for burst water pipes. Here are a few examples:

• U.S. climate and weather agencies synthesize data gathered from ocean buoys, barometer and thermometer readings and satellite images to predict the strength of hurricanes and where cargo ships should dock.
• In the event of a hurricane, given relevant data and insights, county and municipal agencies can determine where they should deploy ambulances ahead of time. This practice is currently in use by FEMA and can apply to any disaster where we need to deploy physical supplies quickly and efficiently.
• In New Orleans, AI-enabled insights prompted teams to order large amounts of lumber in anticipation of the need to rebuild after a hurricane. 
• In Texas earlier this year, utilities needed to make thousands of service calls but lacked the parts to make the necessary repairs. Predictive insights could have helped mitigate some of the more severe supply chain impacts of the event.

Moving forward, as the public sector facilitates stronger partnerships with the technology sector to leverage big data and AI, the focus should be on the speed and relevance of the data they are gathering, particularly as it relates to averting or managing a crisis to achieve the best possible outcomes. 

More Opportunities Ahead

There is a strong opportunity for the technology sector to partner with the public sector to improve threat detection and risk mitigation far beyond reacting to an evolving storm.   

AI and data can also act as wingmen for the public sector, strengthening systems and infrastructure over time. This can result in a broader approach to risk mitigation and resilience. For example, looking at the regional strengths and resources across the U.S.—such as hurricane preparedness in the South, transportation planning in the Northeast, food logistics in the Midwest, and wildfire preparedness on the West Coast—federal agencies and legislators can work with the private sector to leverage insight, past data from the impact of an evolving hurricane or freeze, as well as data through available resources from within these regions to help them better prepare. 

The Good News

The events of the past 18 months have exposed many vulnerabilities in our systems, yet the good news is that we gained clear insight into where we can strengthen infrastructure. Now is the time to incorporate critical event management into continuity and resiliency plans, using accurate intelligence to help us make informed decisions during uncertainty. More direct and rapid cycles of information sharing between federal and state organizations and within agencies—driven by AI and data—can only help create more resilient systems nationwide.