AI Policy Research and Industrialized Construction: Systematic Mapping Review Dataset of 394 Peer-Reviewed Articles (2016-2026)

This dataset accompanies the systematic mapping review titled "AI Policy Research and Industrialized Construction: A Systematic Mapping Review of Sectoral Gaps and Governance Priorities," submitted to the 2026 International Conference on Industrialized Construction (IConIC 2026). The dataset contains 394 peer-reviewed journal articles on artificial intelligence (AI) policy retrieved from Scopus between 2016 and 2026. Records were identified using the query: TITLE-ABS-KEY("AI policies" OR "AI policy" OR "artificial intelligence policy" OR "artificial intelligence policies") AND PUBYEAR greater than 2015 AND PUBYEAR less than 2027, limited to English-language journal articles. An initial pool of 549 records was screened, with 150 excluded for addressing AI policy only marginally, leaving 394 articles for analysis. Each record was coded across 21 variables covering bibliographic information, sectoral domain, policy focus area, geographic focus, research method, research goal, AI technology type, stakeholder perspective, policy stage, journal ranking, key themes, identified gap, and abstract. Consolidated variables (Domain_Sector_Consolidate, Research_Goal_Consolidate, Stakeholder_Perspective_Consolidate, Policy_Stage_Consolidate) provide higher-level groupings used in the published analysis. The dataset supports the figures and tables reported in the IConIC 2026 paper and may be reused for further bibliometric analysis, evidence mapping, or policy research on AI governance across sectors. File: data.csv (UTF-8 encoded, 394 rows, 21 columns)