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The Impact of Artificial Intelligence on Quality and Sustainable Development: a Bibliometric Analysis

Genny Torcoroma Navarro Claro & José A. Bayona

Quality Innovation Prosperity2025https://doi.org/10.12776/qip.v29i1.2151article
AJG 1
Weight
0.37

What the paper says

This bibliometric study aims to analyse the impact of artificial intelligence (AI) on quality and sustainable development. Methodology/Approach: The research employed the InOrdinatio method, complemented by R Studio and the Bibliometrix package, to conduct a comprehensive review of scientific publications from 2000 to 2024. Findings: The results reveal a significant annual growth rate of 25% in scientific production, accumulating 925 documents. AI has been widely applied to optimise organisational quality processes, particularly in manufacturing and technology sectors. Furthermore, AI has contributed to sustainable development by enhancing resource management and promoting sustainable practices. The study highlights strong international collaboration, with China, the United States, and India leading scientific output. Research Limitation/Implication: Despite the increasing convergence of AI, quality, and sustainability, the study identifies gaps in research integration across underrepresented regions and a lack of focus on emerging areas. Originality/Value of paper: This study provides a structured bibliometric analysis, shedding light on the evolving role of AI in enhancing quality management and fostering sustainability. The findings contribute to future research directions by identifying key trends, challenges, and opportunities for innovation.

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https://doi.org/https://doi.org/10.12776/qip.v29i1.2151

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@article{genny2025,
  title        = {{The Impact of Artificial Intelligence on Quality and Sustainable Development: a Bibliometric Analysis}},
  author       = {Genny Torcoroma Navarro Claro & José A. Bayona},
  journal      = {Quality Innovation Prosperity},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.12776/qip.v29i1.2151},
}

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.