Redefining public governance in the advent of generative artificial intelligence
The U.S. public sector is embracing a digital revolution, driven by the combination of generative artificial intelligence (AI) and low-code technologies. This transformation is primarily enhancing legacy system modernization and improving service delivery efficiency.
The outdated systems in the public sector pose a significant challenge to innovation. However, with generative AI, these complex codebases can be analysed, documented, and refactored rapidly, shortening modernization timelines from years to weeks [1]. This accelerated pace allows agencies to transition more smoothly to modern, cloud-based infrastructures.
Moreover, AI is changing the way information is delivered and decisions are made in the public sector. Agencies are developing AI-powered chatbots and constituent engagement tools that answer common public inquiries efficiently, reducing repetitive workloads for government workers and improving resident experiences [2].
The integration of AI with low-code platforms also empowers non-expert staff to create or customize tools rapidly, helping agencies overcome internal capability shortages and budget limitations while scaling up AI adoption responsibly [1][4]. This approach bridges skill gaps and resource constraints, ensuring that agencies can build adaptable systems that can evolve with policy shifts and administrative turnover.
The security and control requirements of the public sector are not overlooked in this digital transformation. The integration of AI with cloud services facilitates scalable, secure, and compliant solutions that meet public sector demands for data sovereignty and regulatory adherence while enhancing service responsiveness [3].
However, the digital transformation of the U.S. public sector is progressing at a slow pace. Approximately 80% of federal IT budgets are allocated to operations and maintenance of existing legacy systems [5]. Public sector teams are often smaller and stretched thin due to budget constraints and high turnover rates. These challenges make long-term planning and technology investments challenging.
Success depends on selecting technologies that deliver not only speed and scale but also the governance and compliance capabilities required to navigate evolving regulations, ethical considerations, and public accountability. The underlying infrastructure of many agencies' digital portals is outdated, causing delays, inefficiencies, and frustration.
Technological advances, particularly generative AI, offer the potential to automate mundane tasks, extract insights from unstructured data, and augment decision-making in real time. Expected advances in multimodal AI, real-time data integration, and cross-agency interoperability will unlock new capabilities, provided agencies have the foundation in place to adopt them.
The rise of AI tools like ChatGPT puts public agencies under pressure to innovate. By harnessing the power of generative AI and low-code technologies, U.S. public sector organizations can modernize legacy infrastructures swiftly, create smarter citizen services, and overcome operational constraints, all driving more efficient, scalable government services.
[1] https://www.forbes.com/sites/forbestechcouncil/2021/05/25/how-ai-and-low-code-are-revolutionizing-government-technology/?sh=75a3a5907854 [2] https://www.whitehouse.gov/briefing-room/statements-releases/2021/05/21/fact-sheet-white-house-announces-new-initiatives-to-achieve-equity-in-artificial-intelligence/ [3] https://www.forbes.com/sites/forbestechcouncil/2021/08/18/how-low-code-is-empowering-public-sector-agencies-to-drive-digital-transformation/?sh=12647c61716b [4] https://www.cio.com/article/3569366/low-code-development-is-transforming-government-it.html [5] https://www.nextgov.com/emerging-tech/2019/12/modernizing-federal-it-legacy-systems-still-consume-80-of-it-budgets/161214/
Artificial intelligence, through its generative capabilities, is quickly analysing and refining complex codebases in the public sector, enabling the modernization of outdated systems in weeks rather than years [1]. Moreover, the integration of AI with low-code platforms empowers non-expert staff to create or customize tools swiftly, bridging skill gaps and resource constraints [4].
