A guest article from Kainos argues that agentic AI can fundamentally change how public services work by allowing agents to interpret policy, plan actions, and interact with systems. The authors use examples like automated house sales and digital twins for policy testing to illustrate how agents can handle complex workflows. They warn that greater autonomy requires trust in people, process, and output to prevent errors and maintain accountability. The piece suggests that assurance must be designed into systems from the start rather than added later. The goal is to earn autonomy through evidence and clear boundaries rather than restricting innovation.
Read the full story at techuk.org.
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