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Public sector innovation

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Public sector innovation
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Report

Making agentic AI work for government: a readiness framework


Agentic artificial intelligence (AI) is driving a fundamental shift in capability, allowing systems to autonomously execute end-to-end, multi-step workflows. This report applies a novel, department agnostic perspective on government activities. It provides a clear approach to assess where agentic AI can deliver the greatest public value and what risks must be managed before deployment at...
Report

The respect story: a political narrative for public service reform


This paper makes the case for narrative as a governing tool. It argues that a growing consensus over public service reform that is preventative and more relational is stalling for want of a story. The paper examines why reform stalls, then makes the case for putting respect at the heart of public service design and...
Report

Designing and delivering employment support


This report examines how employment support for people out of work due to ill health or disability in England can be redesigned to be more effective. It critiques failed centralised models, explores the opportunities and risks of devolving support to local government, and sets out eight recommendations to deliver a renewed, locally led approach to...
Report

Ministerial leadership of public service reform


This paper outlines how ministers can be effective leaders of public service reform and drive change across the system. Drawing on studies of successful public service reform in the United Kingdom, it explores what effective leadership looks like in public service reform, and the lessons this holds for current and future ministers.
Guide

Guidance for AI proof of concept to scale


The purpose of this guidance is to enable Australian Government agencies to move beyond isolated artificial intelligence (AI) experiments and achieve meaningful business AI adoption, ensuring that AI delivers value and is embedded responsibly within government operations and services. It provides practical advice for successfully scaling AI proof of concepts.