Advancing government AI to improve how work gets done
Government agencies are under pressure to deliver faster, clearer service while managing increasing demand and constrained staff. Less than a year after we first launched Government Experience Agent (GXA), the second wave of public sector AI innovation is here, introducing a new approach to AI-powered government services, connecting resident interactions to how work is completed, tracked, and resolved. This shift evolves AI from one-off, isolated interactions into the operational systems that drive service outcomes and resident satisfaction.
AI is already present in government environments — whether through secure, governed tools like GXA or as unapproved shadow IT — and its use is expanding across teams and channels. The central decision for leaders is how to apply it in a way that improves outcomes without introducing risk or fragmentation.
The latest improvements to GXA extend AI beyond question-and-response scenarios into the workflows that define how service is delivered.
Government teams are managing sustained increases in service demand alongside rising expectations for speed, access, and clarity. These pressures affect how work moves every day — how requests are submitted, how they are routed across teams, and how efficiently they reach resolution.
Across agencies, this creates a convergence of operational challenges. Service volume continues to rise without corresponding increases in staff capacity. Residents expect immediate, consistent answers across multiple channels, and internal systems often lack the visibility required to track work as it progresses. These conditions shift the focus from improving isolated touchpoints to improving overall system performance. Service quality now depends on how reliably work moves from request to resolution, and whether that work can be tracked, understood, and defended.
The next phase of AI for government focuses on continuity across the full lifecycle of a service request. In many agencies, delays and inconsistencies are introduced during handoffs between systems and teams. Intake data may be incomplete, status may be difficult to track, and manual steps often accumulate as work progresses.
GXA is evolving to address these conditions by supporting workflow-driven AI agents that operate within existing processes. These agents ensure intake is complete from the start, reduce manual coordination between teams, and maintain clear communication throughout the process. At each stage, staff remain responsible for decisions and oversight, while the system provides the structure needed to keep work moving consistently.
This approach improves reliability by standardizing how work progresses. Each request follows a defined path from submission through completion, with fewer points of failure and greater visibility across the lifecycle.
GXA applies AI as a governed layer across service delivery, ensuring that interactions and operations function as a unified system. Residents engage through voice, web, and messaging interfaces and receive consistent, source-based responses regardless of channel. This consistency expands access and reduces confusion, particularly for users who rely on different modes of engagement.
Beyond access, GXA accelerates how information is retrieved and used. Long-form documents and public records can be accessed directly through plain-language queries, allowing both residents and staff to focus on decisions rather than navigation. This reduces time spent searching and increases clarity around outcomes.
The most significant change is how service requests are created and processed. Guided interactions capture structured, complete information at the point of intake, which allows requests to move directly into execution. Work is routed into the systems where it is completed, ownership is defined, and progress is visible.
This continuity eliminates the gaps that typically occur between intake, routing, and resolution, creating a single, seamless workflow driven by AI while governed by policy and orchestrated by humans.
Current government use cases show that AI delivers the most value in areas where operational friction directly limits service outcomes. In resident self-service, GXA enables direct access to information and guidance, allowing individuals to complete tasks independently and reducing the volume of incoming requests. These interactions improve accessibility while allowing staff to focus on higher-value work.
Within workflow efficiency, structured intake ensures requests are complete and accurate before they enter the system. This reduces the need for follow-up and eliminates common failure points caused by missing or inconsistent data. As requests move forward, teams are able to act immediately, rather than stopping to correct or clarify submissions.
Administrative and compliance-related processes also benefit from this approach. Many of these workflows involve high volumes of repetitive, time-intensive tasks. AI introduces consistency and reduces manual effort, which improves both speed and reliability. In parallel, eligibility and service access become clearer for residents, who can identify relevant services and complete requests within a single interaction, rather than navigating multiple disconnected systems.
GXA includes co-development programs with Granicus customers that allow agencies to apply AI within their own operational context. These programs are designed to ensure solutions reflect real processes and deliver measurable results under actual conditions.
Through these partnerships, agencies identify priority service areas and work alongside Granicus to design and test workflow-driven agents. These agents are then integrated into live environments, where they can be evaluated against operational objectives. This process ensures AI is applied with precision and improvements are grounded in how government work is actually performed.
AI has matured to the point where its value depends on disciplined application. GXA applies that discipline across service workflows, enabling agencies to improve outcomes while maintaining control, accountability, and trust.
When workflows are structured, visible, and governed, service outcomes improve consistently. Residents receive clearer answers and complete tasks with fewer steps because interactions are aligned with how services are delivered. Staff spend less time coordinating work manually and correcting errors because requests enter the system in a complete and usable form. Leaders gain confidence because they can see how work moves and how outcomes are produced.
GXA defines a practical path to applying AI at scale by focusing on operations. Working together, Granicus and our public sector partners are using AI to improve how work is done, which in turn improves the access, satisfaction, and overall experience delivered to the public.