EU AI Act regulation: a study of non-European Union manufacturers' compliance preparedness
Purpose This study investigates the preparedness of manufacturing companies in the UK and Brazil to comply with the European Union's artificial intelligence (AI) Act of 2024. It aims to assess these companies' ability to identify AI-related risks, implement necessary compliance measures and evaluate a newly developed compliance framework designed to enhance regulatory compliance. Design/methodology/approach A mixed-methods approach was adopted. First, 10 AI use case scenarios were identified from the literature related to production processes and products. A survey of 152 members from 87 companies in the UK and Brazil was conducted to gauge baseline readiness. Subsequently, a novel compliance framework was piloted with 11 of these companies. Pre- and post-pilot assessments were analysed to evaluate improvements in risk identification, regulatory knowledge and organisational confidence. Findings The results reveal a significant gap in compliance readiness at baseline and substantial improvements post-intervention. Prior to the pilot, participants on average identified correctly the risk levels in only 40% of scenarios and just 42% demonstrated adequate knowledge of the Act's provisions. After implementing the compliance framework, average risk identification accuracy rose to 86% and regulatory comprehension to 81%, indicating a marked improvement (p < 0.01). Participants' self-reported confidence in managing AI compliance also increased correspondingly. Originality/value This study is among the first to empirically examine AI Act compliance readiness in non-EU manufacturing companies. It provides a novel compliance framework to improve the capacity to manage AI-related regulatory requirements. The study offers valuable insights for manufacturing managers and regulators navigating the interface of technological innovation and regulatory compliance.
Authors
- Tengfei Long (ORCID: https://orcid.org/0000-0002-2981-4812)
- Marcelo Negri Soares (ORCID: https://orcid.org/0000-0002-0067-3163)
- Marcos Kauffman (ORCID: https://orcid.org/0000-0002-5465-2368)
- Welington Júnior Jorge Manzato
- Kuo-Ming Chao
Institutions
- Centro Universitário Cesumar (BR)
- I-Form Advanced Manufacturing Research Centre (IE)
- University of Roehampton (GB)
Publication Details
- Journal
- Journal of Manufacturing Technology Management
- Published
- 2026-01-26
- DOI
- https://doi.org/10.1108/jmtm-07-2025-0657
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00