State and local government call centers become lifelines during and after disasters. Most recently, the state of Florida deployed call centers and hotlines as a key strategy to aid in the recovery efforts following Hurricane Idalia.

These call centers coordinate response efforts, disseminate vital information, provide assistance and emotional support, allocate resources and collect feedback for improvement. 

Unfortunately, many state and local call centers often struggle during and after a disaster with issues such as inadequate technology integration between the front and back offices, inefficient self-service channels, high call volumes, limited staff, communicating complex information quickly and an abundance of manual, repetitive tasks for disaster recovery personnel. 

State and local call centers must also deal with issues related to legacy systems. These can result in dropped calls or the loss of valuable data, thus making it difficult for call center personnel to provide efficient disaster recovery services when people need them the most. 

During crises, state and local government call centers are now turning to automation and artificial intelligence (AI) tools to enhance citizen service delivery and aid in disaster response and recovery.

Resolving aftermath call inquiries more efficiently and faster

AI-powered digital assistance can answer citizen queries 24/7, while AI-powered data dashboards can provide citizens with real-time information from any data source during a disaster and its aftermath, improving how call centers serve the public and reducing the workload for overwhelmed personnel. This capability allows personnel to focus on more complex tasks during disasters, such as guiding callers in distress, offering advice on how to stay safe during and after disaster strikes, providing medical instructions if needed and connecting callers with the appropriate emergency services. 

These tools can also provide fast and consistent customer support, enabling instant assistance without human intervention. AI-powered automation can quickly answer calls and provide pre-recorded messages with relevant information, ensuring callers receive immediate help and reduce the burden on personnel.

In cases where a caller handoff is required, AI delivers crucial information and customer context, guiding the agent with insights and suggesting actions for faster resolutions during a crisis. 

Most importantly, AI-powered automation can intelligently route incoming inquiries based on urgency, topic or complexity. By automatically categorizing and prioritizing requests, these technologies ensure that critical issues receive prompt attention. At the same time, less urgent matters are appropriately addressed. This capability ensures that urgent calls receive immediate attention, reducing response times and potentially saving lives.

Modernizing call centers to avoid relief effort recovery delays

State and local call centers can benefit from using AI-powered automation to create a unified “office” or response center during and after a disaster. This technology easily integrates with user interfaces and application programming interfaces, streamlining processes and enhancing existing call center technology. Furthermore, an automated integration ensures data consistency, integrity and compliance through audit trails while avoiding the challenges of legacy call systems. 

Conducting data analysis for time-sensitive, life-saving caller information 

State and local call centers can deploy AI-powered automation technology to automatically collect and analyze data from various sources, such as social media, emergency services and news outlets. 

AI-powered automation also improves data accuracy and consistency by eliminating manual errors that can occur during high-stress situations, such as a hurricane or wildfire. These capabilities then send the most updated information from callers to disaster relief personnel in a time-sensitive manner by integrating various systems, including historical data and notes. This ensures that critical information is recorded correctly, enabling a more effective response to emergencies.

Devising disaster response strategies and allocating relief resources 

When combined with machine learning (ML), AI and automation can help state and local call centers make real-time data-driven decisions. In this instance, AI-powered automation can analyze call records, provide real-time reporting and analytics, perform trend analysis to identify bottlenecks and compile reports for disaster relief personnel. These capabilities can then provide state and local authorities with valuable intelligence for decision-making when devising disaster response strategies and allocating relief resources. 

Building smarter state and local call centers when time is of the essence

In the future, we can anticipate seamless integration between AI-powered automation and disaster response processes at call centers. AI and automation will be programmed to adapt to changing circumstances and be at the forefront of providing real-time support to citizens and call center agents.

Finally, AI-powered automation will be at the forefront of state and local call center modernization, improving the understanding of customer queries and data, providing accurate responses, eliminating the need for human intervention and greatly enhancing citizen experiences during disasters and their aftermath, when every second counts. 


Todd Schroeder

Todd Schroeder is vice president of public sector at UiPath. An industry professional with 15 years of hands-on experience in public sector technology and leadership, Schroeder has extensive expertise in technology change management, enterprise data management solutions, business intelligence, and big data programs. Prior to joining UiPath, he was vice president of business development of public sector at Celonis, managing director of global public sector strategy and sales at Google, and director of public sector digital strategy at Google.

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