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AI-Enabled Performance Improvement Mechanisms in Chinese Law Firms: A Case Study of the Shanghai Legal Industry
Dissertation

AI-Enabled Performance Improvement Mechanisms in Chinese Law Firms: A Case Study of the Shanghai Legal Industry

Feng Zhu
University of La Verne
Doctor of Business Administration (DBA), University of La Verne
2026

Abstract

AI LAW FIRM LEGAL INDUSTRY PERFORMANCE IMPROVEMENT China
Objective. Taking the legal industry in Shanghai as an example, this study explores the mechanism of AI in improving the efficiency of China’s legal sector and constructs an implementable empowerment framework for AI-driven legal services. Theoretical framework. This research takes the Technology - Organization - Ethics - Regulation (TOER) framework as the core to analyze the dilemmas and optimization paths of AI application. Research methods. Adopting qualitative research, this study collects data from 40 stakeholders through semi-structured interviews, focus groups, observation and documentation, and conducts thematic coding analysis with NVivo. Research findings and conclusions. AI improves work efficiency in legal retrieval, contract review, document generation and other links, yet its application is restricted by AI hallucination, algorithmic opacity, data defects, skill gaps and inadequate regulation. The coordinated promotion from the four dimensions of technology, organization, ethics and regulation can achieve sustainable efficiency improvement. Prospects and suggestions. Future research should focus on the four dimensions of technology, organization, ethics and regulation, based on China’s local practices, to explore AI application paths more suitable for China’s national conditions. Long-term tracking and cross-regional comparative studies can be carried out to continuously improve the theoretical system.
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