A path to follow to overcome foundational barriers to the adoption of artificial intelligence within the manufacturing industry: a conceptual framework
Moacir Godinho Filho, Sofia Almeida, Murís Lage, Lauro Osiro, Bruna Ferreira Cícero Lima, Mário Henrique Bueno Moreira Callefi
Abstract
Despite growing interest, many industries face foundational barriers to AI adoption, especially in emerging economies. This study systematically analyzes these barriers in manufacturing, addressing a critical gap in the literature. Unlike prior research on application-specific challenges, we focus on foundational issues that must be resolved for effective AI implementation. Using Interpretive Structural Modeling (ISM) and fuzzy MICMAC, we develop a four-level framework identifying 20 key barriers. Our framework provides actionable steps for managers, emphasizing workforce reskilling, Enterprise Information Systems (EIS), and Industry 5.0 principles. This study offers practical insights to help industries navigate AI adoption challenges.