From Digital to AI-Enabled Public Innovation: A Theoretical Framework for AI-Era Government
Keywords:
Keywords: Composable Architecture, Platform Theory, Network Effects, Hyperscale Innovation, API-First Government, Complexity Theory, Digital GovernanceAbstract
While traditional theories of public administration (e.g., Weberian bureaucracy, New Public Management, and Digital-Era Governance) offer foundational insights into public value, equity, and accountability, they lack conceptual mechanisms to explain the architectural requirements of digital-native governance. This paper presents Government Stack 2.0 (GovStack 2.0), a theoretical framework applying platform architecture principles to conceptualize government as a composable, API-first ecosystem. Drawing from modularity theory, network economics, and platform governance literature, we define a four-layer architectural abstraction: Infrastructure-as-a-Service (IaaS-Gov), Intelligence-as-a-Service (IntelaaS), Process-as-a-Service (PaaS-Gov), and Experience-as-a-Service (XaaS-Gov). We establish precise boundaries distinguishing GovStack 2.0 from digital public infrastructure (DPI) and existing digital government concepts. Furthermore, we qualify the application of Metcalfe’s Law in the public sector by modeling positive, negative, and asymmetric network externalities under administrative and institutional constraints. Finally, we formalize "hyperscale public innovation" as a set of theoretical propositions subject to empirical validation.
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