Governments increasingly deploy AI in public services, making transparency essential for accountability and public trust. Australia's Standard for AI Transparency Statements (AITS) requires government bodies to disclose how AI is used in practice, yet little empirical evidence exists on how these requirements are realised in documents. This paper presents a government AITS dataset, dubbed AITS-101, and provides one of the first systematic analysis of their content. Using stylometric, quantitative, and qualitative document analyses, we examine disclosure coverage, structure, and recurring patterns. Our findings reveal substantial variation in AI-related practice disclosure, highlight gaps between policy intent and implementation, and inform the design of more effective public-sector AI transparency standards.

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