Autonomous vehicles and Quality 5.0: a conceptual paper on the role of artificial intelligence providers

Purpose AI-based autonomous vehicles (AVs) are a promising Industry 5.0 solution, but their diffusion is limited due to shared concerns that quality management can help to overcome. Quality 5.0 is a new approach in the literature that ensures respect for human and environmental safeguards, as well as for societal and industrial development. The novelty of this concept warrants further research. This work conceptualizes the promotion of Quality 5.0 in the AVs industry by presenting it from an often under-investigated perspective: the role of artificial intelligence (AI) providers. Design/methodology/approach This conceptual paper outlines the main actions by which AI providers can be Quality 5.0 enablers in the AVs industry. By integrating current literature on smart mobility, AI, AVs and Quality 5.0, this study provides theoretical propositions and a conceptual framework. Then it presents an illustrative case of an existing AI provider market leader. Findings AI providers within AVs industry enable Quality 5.0 by developing technical subsystems that support Quality 5.0 components, adopting a holistic approach to data infrastructure management, leveraging generative physical AI and building a network around it. Originality/value This paper contributes to the current debate on Quality 5.0 by presenting an underexplored perspective on quality management and the AI-based AVs industry: the AI provider's role as enabler of Quality 5.0.

Authors

Institutions

Publication Details

Journal
The TQM Journal
Published
2026-06-26
DOI
https://doi.org/10.1108/tqm-12-2025-0730
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Autonomous vehicles and Quality 5.0: a conceptual paper on the role of artificial intelligence providers

Francesco Schiavone, Annaluce Mandiello
The TQM Journal
Digital Transformation in Industry
article

Autonomous vehicles and Quality 5.0: a conceptual paper on the role of artificial intelligence providers

Francesco Schiavone, Annaluce Mandiello
article en

Abstract

Purpose AI-based autonomous vehicles (AVs) are a promising Industry 5.0 solution, but their diffusion is limited due to shared concerns that quality management can help to overcome. Quality 5.0 is a new approach in the literature that ensures respect for human and environmental safeguards, as well as for societal and industrial development. The novelty of this concept warrants further research. This work conceptualizes the promotion of Quality 5.0 in the AVs industry by presenting it from an often under-investigated perspective: the role of artificial intelligence (AI) providers. Design/methodology/approach This conceptual paper outlines the main actions by which AI providers can be Quality 5.0 enablers in the AVs industry. By integrating current literature on smart mobility, AI, AVs and Quality 5.0, this study provides theoretical propositions and a conceptual framework. Then it presents an illustrative case of an existing AI provider market leader. Findings AI providers within AVs industry enable Quality 5.0 by developing technical subsystems that support Quality 5.0 components, adopting a holistic approach to data infrastructure management, leveraging generative physical AI and building a network around it. Originality/value This paper contributes to the current debate on Quality 5.0 by presenting an underexplored perspective on quality management and the AI-based AVs industry: the AI provider's role as enabler of Quality 5.0.

The TQM Journal
Parthenope University of Naples (IT)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Digital Transformation in Industry
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.