IDC research shows that the transformation of agentic AI -- autonomous digital workers that can reason and take action -- in government includes three focus areas: operational orchestration, citizen service delivery, and decision support for policy and planning.

Operational orchestration refers to agent-driven systems that coordinate multi-step workflows across departments, improving service delivery speed and scale. Citizen service delivery is enhanced with agents that can deliver proactive, context-aware, and personalized interactions. Agentic AI can also use synthetic data and model scenarios to enhance the planning and delivery of new services by providing more contextual intelligence around stakeholder needs.

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Recent research shows that agentic AI scaling is predicated on a strong data foundation, including government agencies' ability to identify high-impact workflows to agentify and the implementation of a data architecture for AI agents. In addition, government agencies must ensure that data quality and accessibility are in place. Lastly, government agencies must build an operation and governance model for agentic AI -- this is about rethinking how work gets done.