From AI Adoption to Institutional Preparedness: Governing Enterprises for AGI
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Dongshin University
Abstract
Artificial general intelligence (AGI) is increasingly discussed not merely as a technical frontier but as a social and institutional challenge. Drawing on current generative and agentic AI as diagnostic evidence, this paper examines enterprise institutional preparedness for increasingly general and autonomous AI systems through three interrelated dimensions: organizational resilience, employee protection, and social responsibility. Using conceptual and normative analysis, the paper synthesizes AI governance, organizational resilience, labor studies, corporate social responsibility, and policy frameworks to develop a forward-looking governance architecture. The framework links three levels of institutional exposure: continuity of organizational functions, preservation of worker agency, and external social legitimacy. It identifies seven preparedness components: strategic foresight, governance architecture, risk and impact assessment, human oversight, employee protection, social responsibility, and continuous learning. The analysis further distinguishes scalable risks already visible in current AI from potentially discontinuous risks associated with greater autonomy and cross-domain integration. The study shifts the unit of analysis from tool-level AI risk management to enterprise-level institutional capacity to preserve organizational continuity, worker agency, and external social legitimacy.
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