The increasing deployment of agentic artificial intelligence (AI) systems and decentralized digital infrastructures has challenged traditional assumptions about organizational administration, control, and governance. While AI has advanced task-level optimization and decision support, administrative functions such as coordination, compliance, and accountability remain largely centralized and dependent on humans. This paper introduces Autonomous Administrative Intelligence (AAI), a governance-aware AI capability that enables autonomous agents to execute and adapt administrative decisions within strategically defined constraints and decentralized governance mechanisms. Building on the Strategic Decentralized Resilience–AI (SDRT-AI) framework, the study develops a layered architecture and operational flow integrating agentic decision-making, governance-aware learning, and protocol-based validation. The proposed framework explains how strategic intent, organizational capabilities, and decentralized trust jointly enable scalable administrative autonomy while preserving accountability and control. By reframing administration as an AI-mediated governance process, this paper extends research on agentic AI and contributes to administrative science by providing a conceptual foundation for the design and governance of autonomous administrative systems in decentralized organizations.
Aravindh Sekar (2026) studied this question.