Building smarter, stronger communities with an AI-enhanced government workforce

There are an estimated 20.3 million public sector employees in the United States, representing a significant 13% of the country’s active workforce. The implications for turnover are staggering, as several thousand of these employees retire each year on average as others constantly join. Technologies once relied on to manage this process and reduce knowledge loss are no longer able to do so in an efficient, transparent way—skyrocketing costs, zapping institutional knowledge and worse.

Thankfully, the advent of artificial intelligence (AI) in the public sector is here to help. Leading technology analysts predict that by 2026, more than 70% of government agencies will employ AI to augment human decision-making.

In an era characterized by workforce shortages, limited budgets and escalating demands for rapid service delivery, government agencies are frequently hampered by antiquated technology infrastructures that AI-driven technologies are tactfully modernizing. On the ground, that means enhancing field operations, automating workflows, refining budgeting practices and improving resident assistance, setting the stage for a future-ready government workforce that can efficiently meet the needs of its community.

However, with governments facing a labyrinth of technological and organizational challenges standing in the way of AI integration, our work is far from finished.

Today, many agencies are entangled in legacy systems that resist integration with modern AI solutions. Privacy and security of data is another critical concern, as AI systems managing large volumes of sensitive information must comply with stringent data protection laws to maintain public trust. Finally, traditional budgeting often falls short in prioritizing and adequately funding essential programs, a gap that AI-powered budgeting aims to fill by aligning resources more closely with community needs.

To transcend these challenges, we need to follow the examples of several AI-driven solutions available now that have been identified and implemented with promising results. Mobile field operations platforms powered by AI have transformed fieldwork by automating data collection and reporting, thus minimizing the time inspectors need to spend on-site, as shown by the New Jersey Department of Environmental Protection’s significant decrease in inspection times.

Automated document processing systems, as those implemented in Tarrant County, Texas, and Palm Beach County, Fla., expedite the handling of documents and relieve backlogs, leading to substantial time and cost savings. In prioritizing financial resources, AI-driven, priority-based budgeting systems allow for strategic financial decisions, like those seen in Washington County, Wisc., where funding was realigned to support shifting priorities effectively. Moreover, AI virtual assistants are revolutionizing customer service by handling routine inquiries and allowing 24/7 access to information, thus reducing the load on human staff.

It’s clear that effective integration of AI not only addresses immediate challenges of workforce limitations and financial constraints but also establishes a foundation for continual improvement in service delivery, which enhances public trust and engagement. To successfully integrate AI, a phased approach beginning with comprehensive stakeholder engagement and pilot testing is critical. This also mitigates resistance and integrates feedback from workers in the field for smoother implementation.

As we stand on the brink of a new technological era, the message for government agencies is clear: the future is now, and the future is AI. Governments that hesitate to adopt these technologies risk falling behind, unable to meet the evolving demands of the public sector. Adopting AI is no longer an option but a necessity for developing efficient, transparent and responsive government operations.

Jeff Green is the chief technology officer with Tyler Technologies. He started his career with Tyler more than 20 years ago as a software engineer. Green held a variety of leadership roles at Tyler, including director of development, director of operations and vice president of development. He advanced to the position of senior vice president of development for Tyler, where he was instrumental in creating the agreement with Microsoft for the public sector version of Dynamics AX®. As Tyler’s CTO, Green formulates Tyler’s technical vision and leads our development teams to help realize Tyler’s strategic product initiatives. Prior to joining Tyler, Green was a neuroscience researcher and instructor at Grinnell College. He holds a BA degree in psychology from Grinnell College.