Is Your Data Ready for AI? What Five Years of Reports from 26 Regulators Reveal About Data and AI Governance

Working paper reporting, in brief, a document study of the complete College Performance Measurement Framework (CPMF) record of the 26 health regulatory colleges of Ontario, Canada, for 2020–2024 (129 college-years: 128 reports and one council briefing). Each report was scored on a nine-dimension data and AI governance rubric, and all 1,030 forward-looking commitments were traced across the five reporting cycles. In brief: regulators report completing 56% of what they commit to and about one commitment in five is carried over unfinished; data quality is the least-described dimension; no report describes an AI impact assessment or monitoring of AI in use; and once data capability is taken into account, organizational size explains much less of which commitments get stuck. Version 2.0 adds a blind consistency check of the coding on a stratified 23% sample (reported completion κ = 0.82, trajectory κ = 0.73, rubric weighted κ = 0.92; two dimensions below target). Detailed results are reserved for the full report. The codebook, scoring anchors, coded register and regulator-level results are not included. Findings are provisional. Conducted by Adelaide Advisory Group Inc., which provides consulting services to regulators.