迈向智能原生:智能原生企业分级评估框架和战略重点OA

With the elevation of the"AI+"initiative to a national strategy,enterprise intelli-gence is undergoing a fundamental transition from tool-based adoption toward native reconstruc-tion,giving rise to a new organizational form:the AI-native enterprise.Unlike traditional firms that treat artificial intelligence as an auxiliary technology,AI-native enterprises embed AI deeply into their organizational architecture,operational processes,and value-creation logic,achieving a paradigm shift from linear"+AI"enhancement to exponential"AI×"growth.This study aims to clarify the conceptual connotation of AI-native enterprises,develop a systematic maturity assessment framework,and identify strategic priorities for enterprise evolution toward AI nativeness.Methodologically,the study integrates theories of technological innovation,organi-zational management,and context-driven innovation to construct a Technology—Organization—Context(TOC)maturity assessment framework.Based on this tripartite perspective,the paper proposes an AI-native maturity ladder consisting of five levels(L0—L4),ranging from tradi-tional enterprises to fully AI-native enterprises.The framework emphasizes the dynamic interac-tion among technological capabilities,organizational structures,and scenario development,con-ceptualized as a self-reinforcing"intelligence flywheel"that drives continuous learning,adapta-tion,and value creation.The analysis reveals that AI-native enterprises exhibit"born-with-AI"characteristics,where AI functions as organizational DNA rather than a supplementary tool.At lower maturity levels,enterprises rely on fragmented AI tools and hierarchical governance,with limited scenario innovation.As maturity increases,firms progressively establish unified data in-frastructures,human—AI collaborative decision-making mechanisms,and context-driven value creation models.Fully AI-native enterprises achieve autonomous evolution,liquid organiza-tional forms,and ecosystem-based value co-creation,enabling AI to define products,processes,and business models endogenously.The study further identifies key strategic priorities for AI-native evolution.Enterprises should avoid"AI-for-AI's-sake"approaches and instead adopt a value-oriented path characterized by scenario anchoring,system-level reconstruction,and hu-man—AI symbiosis.Importantly,progress across the TOC dimensions need not be synchronous;firms should leverage their unique resource endowments to identify high-impact entry points while maintaining dynamic balance among technology,organization,and context.The research contributes theoretically by advancing a structured maturity model for AI-native enterprises and practically by offering actionable guidance for firms navigating intelligent transformation.It un-derscores that AI-native evolution is not merely a technological upgrade but a profound organiza-tional metamorphosis essential for sustainable competitiveness in the intelligent economy era.