The AI Efficiency Trap: Why Local Automation Gains Fail to Become Organizational Value

Authors

  • Renzhong Li CEIBA Business School, Hong Kong Author

DOI:

https://doi.org/10.63029/tz21n342

Keywords:

artificial intelligence, organizational value, organizational complementarity, omnichannel integration, human–AI collaboration, digital transformation, business process management

Abstract

Artificial intelligence can deliver substantial task-level efficiency gains without generating equivalent organizational value. This Research Note conceptualizes this disconnect as the AI efficiency trap and introduces conversion loss as the mechanism through which local gains dissipate across organizational value flows. Four forms of conversion loss are identified: coordination, continuity, verification, and governance loss. Building on research on IT business value, digital transformation, AI capability, omnichannel integration, and human–AI collaboration, the paper develops a value-conversion framework. It argues that organizational complementarity, task-appropriate omnichannel integration, human–AI task fit, and end-to-end outcome feedback determine whether AI-enabled efficiencies survive their transmission into customer, business, and risk outcomes. The framework shifts attention from AI adoption toward the organizational conditions required for value realization at scale.

Author Biography

  • Renzhong Li, CEIBA Business School, Hong Kong

    Renzhong Li holds a Doctor of Business Administration degree and is an associate researcher at CEIBA Business School. He currently serves as Head of the General Office and the Board of Directors' Office of China United Property Insurance Company Limited, and also holds the positions of Vice Chairman of the Trade Union and Employee Director. He is a Strategic Expert of the Statistics and Research Committee of the Insurance Association of China, and an Industry Mentor for master's students at Zhongnan University of Economics and Law. He is the author of the academic monograph "Consumer Response-Driven Omnichannel Integration" (China Financial Publishing House), and has published a theoretical article entitled "Rebuilding Risk-Control Resilience for the High-Quality Development of the Property Insurance Industry" in China Finance, a Chinese core journal (Peking University edition).

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Published

2026-09-30

How to Cite

Li, R. (2026). The AI Efficiency Trap: Why Local Automation Gains Fail to Become Organizational Value. Management Research Quarterly, 3(2), 36-42. https://doi.org/10.63029/tz21n342

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