Competitiveness of Artificial Intelligence's (AI) Technology-Adoption in the Healthcare Sector in China: An Expert Analysis

This research examined China’s three-tier national hospital system to understand how Artificial Intelligence (AI) technology influences unit-level competitiveness in both clerical and clinical functions. Through content analysis, the study found that the sector currently operates at the level of artificial narrow intelligence. Experts largely agreed that its adoption has been driven by the need to meet hospitals’ unitary requirements. Fragmentation emerged as the dominant paradigm in experts’ perspectives, with four distinct clusters of opinion reflecting stakeholder-specific, compartmentalized views of AI’s utility. While sentiment was divided, it remained broadly positive, shaped by two key rupture factors: (i) the varying cultural and technical readiness across hospitals, and (ii) the paradoxical allocation of financial resources within the current national public funding framework-perceived as disproportionate to each unit’s specialization and thereby constraining further investment in AI initiatives.

Authors

Publication Details

Journal
Cureus Journal of Business and Economics.
Published
2025-11-27
DOI
https://doi.org/10.7759/s44404-025-08306-9
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Competitiveness of Artificial Intelligence's (AI) Technology-Adoption in the Healthcare Sector in China: An Expert Analysis

Nélson António, Bruno F. Abrantes, Virgínia Trigo, Xiang Shui Miao
Cureus Journal of Business and Economics.
Artificial Intelligence in Healthcare and Education
article

Competitiveness of Artificial Intelligence's (AI) Technology-Adoption in the Healthcare Sector in China: An Expert Analysis

Nélson António, Bruno F. Abrantes, Virgínia Trigo, Xiang Shui Miao
article en

Abstract

This research examined China’s three-tier national hospital system to understand how Artificial Intelligence (AI) technology influences unit-level competitiveness in both clerical and clinical functions. Through content analysis, the study found that the sector currently operates at the level of artificial narrow intelligence. Experts largely agreed that its adoption has been driven by the need to meet hospitals’ unitary requirements. Fragmentation emerged as the dominant paradigm in experts’ perspectives, with four distinct clusters of opinion reflecting stakeholder-specific, compartmentalized views of AI’s utility. While sentiment was divided, it remained broadly positive, shaped by two key rupture factors: (i) the varying cultural and technical readiness across hospitals, and (ii) the paradoxical allocation of financial resources within the current national public funding framework-perceived as disproportionate to each unit’s specialization and thereby constraining further investment in AI initiatives.

Cureus Journal of Business and Economics.
Southern Medical University
Openalex Percentile: Top 70%
Artificial Intelligence in Healthcare and Education
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