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

Sep 2026 · F1000Research · 0 citations · 75 references

TL;DR

The SLR demonstrates that effective AI and digital platform governance demands a holistic, context-sensitive approach that actively balances efficiency with justice, innovation with accountability, and risk with public value.

Abstract

The integration of Artificial Intelligence (AI) and digital platforms into public administration and private sectors is fundamentally reshaping governance structures worldwide. While these technologies offer substantial opportunities for efficiency and innovation, they simultaneously pose significant challenges to legal accountability, institutional legitimacy, social equity, and ecological sustainability. Despite a proliferation of policy initiatives, comprehensive evidence is lacking on how AI-driven governance concretely influences policy decision-making across diverse strategic sectors. This study employed a systematic literature review (SLR) methodology, following a structured screening and selection process. From an initial corpus, 45 peer-reviewed empirical and policy-oriented articles published between 2021 and 2026 were selected for in-depth analysis. A thematic synthesis approach was applied, categorizing the literature into four interconnected analytical pillars: (i) institutional transformation and regulatory governance, (ii) access, participation, and digital justice, (iii) innovation, competitiveness, and sustainable development, and (iv) ethics, risk mitigation, and policy legitimacy. The findings reveal that digital governance operates through four primary mechanisms: restructuring institutional procedures and oversight frameworks (law and public administration); enhancing access to resources, services, and citizen participation (agrarian and socio-cultural sectors); driving economic innovation and environmental sustainability (economic and resource management); and navigating ethical risks to maintain policy legitimacy (cross-cutting). A persistent gap was identified between technological adoption and the adaptive capacity of existing legal and regulatory institutions, particularly in addressing data governance, accountability, and inclusivity challenges. The SLR demonstrates that effective AI and digital platform governance demands a holistic, context-sensitive approach that actively balances efficiency with justice, innovation with accountability, and risk with public value. The study offers an integrative framework for policymakers and practitioners to navigate digital transformation complexities and establishes a robust foundation for future empirical research on policy decision-making in the digital era.

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