The Ubiquity Problem in Enterprise AI: Occupational Embedding as Management Innovation and the Relocation of Strategic Advantage
DOI:
https://doi.org/10.65166/21fmda70关键词:
artificial intelligence, occupational embedding, management innovation, competitive advantage, dynamic capabilities, resource-based view, organizational capability摘要
Artificial intelligence (AI) is diffusing through enterprises primarily by being incorporated into existing occupations rather than through the creation of dedicated AI roles. Labor-market indicators suggest that most AI-related demand now arises within established jobs, yet enterprise AI strategy continues to emphasize the acquisition of specialist talent and technology. This paper examines how the occupational embedding of AI reshapes the sources of enterprise capability and competitive advantage, and what organizational conditions allow firms to convert diffuse applied AI use into strategic value. The paper is an integrative conceptual review of literature on AI diffusion, the task content of work, organizational complements, contextual heterogeneity, and competitive advantage. It interprets this literature through resource-based, dynamic-capabilities, absorptive-capacity, and management-innovation perspectives. On that basis, it distinguishes the diffusion of AI use from its organizational integration. This distinction yields a typology of four deployment architectures: peripheral, specialist-centric, diffuse-unmanaged, and integratively embedded. The paper identifies work redesign, complementary skill formation, and integrative coordination as the conversion mechanisms through which distributed use becomes organizational capability, and it frames occupational embedding as a form of management innovation. It further articulates a “ubiquity problem”: as access to general-purpose AI tools converges among competitors, the technology itself becomes an unlikely source of sustained advantage. Advantage instead relocates to the organizational architecture of AI use, which is harder to imitate because of its causal ambiguity, social complexity, and path dependence. Six propositions specify these relationships and their boundary conditions for future empirical testing. The paper concludes that AI strategy is substantially a problem of organizational design, and it offers implications for talent strategy, governance of employee-initiated AI use, and the measurement of AI capability.
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