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Artificial Intelligence (AI)

Alternative labels
Generative AI (GenAI)
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Artificial Intelligence (AI)
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Report

What’s
top of mind
for public servants in 2025


This report shares insights from public servants about their work in government – what’s getting in the way, where they need support and what they want to see done differently. It distils the most relevant insights, maps priorities and considers the skills and knowledge needed to succeed. The report identifies five themes shaping public service...
Briefing paper

Issues and insights, 48th Parliament


A collection of 12 short analyses examining some of the most pressing issues and policy questions facing the 48th Parliament. Each article gives a high-level perspective of significant public policy issues, covering background, context and legislative history, as well as some of the policy and legislative directions raised in the public debate.
Report

The adoption of artificial intelligence in firms: new evidence for policymaking


Artificial intelligence (AI) could help to address sluggish productivity growth in OECD countries. This report provides evidence for policymakers, business leaders and researchers to help understand the adoption of AI in enterprises and the policies needed to enable this. Achieving higher rates of AI adoption could raise labour productivity and have other desirable outcomes.
Report

Trust, attitudes and use of artificial intelligence

Alexandria Macdade, Gerard Hassed

A comprehensive global study into the public’s trust, use and attitudes towards artificial intelligence (AI). The report presents attitudes towards AI in society, at work and in education. It finds that the responsible use and governance of AI is not keeping pace with adoption. The report is accompanied by a snapshot of Australia insights.
Report

AI-assisted vs human-only evidence review


This report describes an exercise to investigate the robustness and reliability of using generative AI to help produce rapid evidence reviews. The AI-assisted output was completed in 23% less time than the human-only output but was judged to be less fluent and required more revisions.