The institutional stack: Realigning U.S. AI governance

Artificial Intelligence (AI) is rapidly reshaping societal structures and democratic institutions, posing a dual governance challenge: harnessing innovation while addressing risks such as algorithmic bias, market concentration, infrastructure inequality, and declining public trust. This paper investigates the adequacy of current U.S. and global AI governance approaches in addressing these challenges. Using institutional theory and socio-technical systems analysis, this research draws on qualitative data through early 2026. The analysis applies a novel “Institutional Stack”—a five-layer socio-technical governance framework comprising Physical, Logical, Application, Market, and Social domains—to map the AI governance landscape. Findings reveal a coordination gap between technological development and institutional oversight. While federal initiatives such as Project Stargate expand the Physical Layer and strategic AI infrastructure, Application Layer safeguards remain fragmented across executive action, state laws, sectoral enforcement, and voluntary industry commitments. Comparative analysis shows that global models, including the EU's risk-based approach, the UK's sectoral model, and China's centralized control, offer useful lessons but entail trade-offs among clarity, adaptability, innovation, enforcement, and civil liberties. International efforts such as the Bletchley Declaration and the G7 Hiroshima Process promote shared norms but remain limited by voluntary implementation, while mechanisms such as judicial review, self-regulation, market competition, and public-private partnerships provide useful but partial safeguards. In response, this paper proposes a Hybrid Governance Framework for the U.S., integrating five pillars: (1) strategic public investment for the Physical Layer, (2) adaptive regulatory standards for the Logical Layer, (3) existing legal remedies for the Application Layer, (4) antitrust oversight for the Market Layer, and (5) public-interest principles for the Social Layer. By aligning formal mechanisms with informal norms, matching governance tools to layer-specific risks, and clarifying mechanisms for cross-layer coordination, this framework balances market agility with democratic accountability, offering a novel synthesis for policy design in a technologically dynamic era.