Global Artificial Intelligence Indicator Database (GAID), 1998–2025

Overview: The Global Artificial Intelligence Indicator Database (GAID) is a longitudinal panel dataset providing the most comprehensive, harmonized overview of the global AI landscape currently available. Spanning 1998 to 2025, GAID integrates, standardizes, and surgically cleans high-fidelity indicators from the world’s three premier AI monitoring authorities: Stanford's AI Index, OECD.ai (AI Policy Observatory), and the Global Index on Responsible AI (GIRAI). Surgical Data Quality & Integrity: Unlike raw index exports, GAID has undergone a rigorous 123-step "clinical" cleaning and deduplication protocol to ensure 100% data integrity. Key technical enhancements include: 1) Harmonized Longitudinal Structure: Multi-source data is consolidated into a "Long Format" (Tidy Data), optimized for immediate ingestion into R, Stata, Python, and SPSS. 2) Universal ISO3 Mapping: 251,676 observations for 214 countries and territories are mapped to standardized ISO3 alpha-3 codes, ensuring perfect join-compatibility with World Bank, IMF, and UN databases. 3) Total Data Completeness: The dataset is 100% complete across all core fields (e.g., Year, Country, ISO3, Metric, Value, Source, Source_Category). 4) Surgical Purging: All sub-national data, non-standard regional aggregates, and encoding artifacts have been removed to provide a pure, national-level research environment. Expanded Dataset Scope: 1) Temporal Range: 1998 – 2025 2) Geographic Scope: 214 Countries/Territories 3) Indicator Density: 24,323 unique metrics (up from 203 in previous versions), providing unparalleled granular detail. 4) Observation Count: 251,676 verified rows. Thematic Domains Include: 1) Research and Development: Publication counts, Field-Weighted Citation Impact (FWCI), arXiv submissions, and patent intensity. 2) Economy & Labor: AI hiring indices (relative to 2016 baselines), skill penetration, industrial robotics growth, and investment values. 3) Enterprise Adoption (OECD): Percentage-based metrics on AI use, big data analysis, cloud computing, and ICT security incidents across specific industry sectors and employee size classes. 4) Education: CS/Informatics graduation and enrollment trends, including per-capita growth rates. 5) Responsible AI (GIRAI): National AI strategy alignment with OECD principles, governance frameworks, and government action coefficients. 6) Public Opinion: Standardized sentiment and trust levels mapped to exact survey question statements (2022–2025). Technical Usage Note: Researchers are advised to consult the accompanying codebook (i.e., CODEBOOK_MASTER_AI_DATA.pdf) for precise data ranges, units of measure (Percentage vs. Ratio vs. Count), and descriptive definitions for the 24,000+ metrics. (Version: 8.28)