Governing AI and Digital Platforms: A Systematic Literature Review of Multi-Sectoral Policy Decision-Making

This dataset supports the systematic review article "Governing AI and Digital Platforms: A Systematic Literature Review of Multi-Sectoral Policy Decision-Making", which synthesises evidence from forty-five (45) empirical and policy-oriented studies examining how Artificial Intelligence (AI) and digital platforms influence policy decision-making processes across legal, agrarian, economic, and socio-cultural governance sectors. The review covers multiple digital technologies and governance frameworks including algorithmic governance systems, AI-enabled judicial platforms, digital public service infrastructures, rural digitalization policies, fintech and digital banking innovations, smart city mobile payment ecosystems, satellite imagery analytics for agricultural credit, open banking APIs, blockchain traceability, biometric attendance systems, government AI transparency statements, health management information systems, and digital land certification platforms across institutional contexts including national governments (G-20 nations, BRICS), regional governance bodies (European Union, African Union, ASEAN), central government agencies (ministries, courts, regulatory authorities), local governments (provincial, municipal, and county levels), and community-level institutions (villages, traditional governance structures, and civil society organizations). The dataset includes: Figure 1 (PRISMA 2020 Flow Diagram) illustrating the study selection process from 6,756 initial records to 45 included studies. Supplementary Document 1 (PRISMA 2020 Checklist) with 27 items completed for the systematic review. Supplementary Document 2 (Risk of Bias Assessment Criteria) detailing the Mixed Methods Appraisal Tool (MMAT) Version 2018 quality appraisal criteria and scoring system applied to 45 studies across qualitative, quantitative, and mixed-methods designs. Supplementary Document 3 (Full Data Extraction Form) containing standardised data from all 45 included studies including author(s), year, sector classification, country/region, study objective, methodology, population/sample, digital technology examined, key findings, MMAT score, and thematic classification. Supplementary Document 4 (Complete Search Strings and Retrieval Results from Scopus Database) including Boolean operators, filters applied (Year: 2021–2026; Document Type: Article; Language: English; Source Type: Journal; Access Type: Open Access), and retrieval numbers by screening stage (initial records: 6,756; after filters: 1,608; title/abstract screening: 93; full-text eligibility: 50; final included: 45). Supplementary Document 5 (Risk of Bias Assessment Results) containing the complete MMAT quality assessment results for all 45 included studies, including individual study scores (5/5 or 4/5), quality ratings (High), and detailed justifications for each study's methodological rigor and risk of bias. All files are available under a Creative Commons Zero (CC0 1.0) license.