Impact of artificial intelligence adoption on quality management in service organizations: A multi-case study

This study empirically examines the effects of artificial intelligence (AI) integration into quality management (QM) processes of service organizations. A multi-case study in service organizations of different types was conducted. We utilized multiple sources of evidence to analyze and triangulate findings, yielding the development of propositions in light of the Dynamic Capabilities theory. Our findings indicated that AI adoption positively supports QM, especially in terms of the organization’s ability to quickly learn and create new quality control and assurance solutions/procedures from this learning (sensing), and to integrate them into organizational processes and routines (seizing). The identification of the impact of AI adoption on QM helps service organizations anticipate potential issues and address adequate countermeasures to reinforce their QM processes towards superior performance results.

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Publication Details

Journal
Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona)
Published
2026-03-23
Primary Topic
Big Data and Business Intelligence
Type
article
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article

Impact of artificial intelligence adoption on quality management in service organizations: A multi-case study

Daniel Luiz de Mattos Nascimento, Paolo Gaiardell, Juan Manuel Maqueira Marín, Moacir Godinho Filho et al.
Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona)
Big Data and Business Intelligence
article

Impact of artificial intelligence adoption on quality management in service organizations: A multi-case study

Daniel Luiz de Mattos Nascimento, Paolo Gaiardell, Juan Manuel Maqueira Marín, Moacir Godinho Filho, Jose Moyano Fuentes, Guilherme Luz Tortorella
article en

Abstract

This study empirically examines the effects of artificial intelligence (AI) integration into quality management (QM) processes of service organizations. A multi-case study in service organizations of different types was conducted. We utilized multiple sources of evidence to analyze and triangulate findings, yielding the development of propositions in light of the Dynamic Capabilities theory. Our findings indicated that AI adoption positively supports QM, especially in terms of the organization’s ability to quickly learn and create new quality control and assurance solutions/procedures from this learning (sensing), and to integrate them into organizational processes and routines (seizing). The identification of the impact of AI adoption on QM helps service organizations anticipate potential issues and address adequate countermeasures to reinforce their QM processes towards superior performance results.

Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona)
Openalex Percentile: Top 6%
Big Data and Business Intelligence
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