A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0
Industry 4.0 is driving significant transformations, even in complex and uncertain industrial environments. This concept represents an innovation strategy aimed at redefining the manufacturing sector, enhancing global competitiveness through cost reduction, more agile processes, and superior produc...
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| Format: | Article |
| Language: | English |
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Centro Latinoamericano de Estudios en Informática
2025-02-01
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| Series: | CLEI Electronic Journal |
| Online Access: | https://clei.org/cleiej/index.php/cleiej/article/view/743 |
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| _version_ | 1825208873025273856 |
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| author | Maria Amelia Eliseo Leonildo Carnevalli Junior Ismar Frango Silveira |
| author_facet | Maria Amelia Eliseo Leonildo Carnevalli Junior Ismar Frango Silveira |
| author_sort | Maria Amelia Eliseo |
| collection | DOAJ |
| description |
Industry 4.0 is driving significant transformations, even in complex and uncertain industrial environments. This concept represents an innovation strategy aimed at redefining the manufacturing sector, enhancing global competitiveness through cost reduction, more agile processes, and superior product quality. Concurrently, Artificial Intelligence (AI) is at the forefront of a profound shift in organizational management and operations, reshaping professional routines and redefining society's interaction with technology. The increasing complexity of business environments, particularly the inherent challenges within industrial sectors, alongside continuous technological advancements, establishes AI as a critical tool not only for fostering innovation but also for optimizing efficiency and enhancing competitiveness across all organizational domains. In this context, this study introduces a structured model grounded in the theoretical exploration of Industry 4.0 maturity models to assess the current maturity levels of AI utilization in the industry. Thus, this work presents the development of a standard for measuring AI adoption levels in Industry 4.0. This index will illuminate companies’ readiness and proficiency in integrating AI into both daily operations and strategic processes. Through the continued application of this tool, companies will also gain insights into their growth across the evaluated domains.
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| format | Article |
| id | doaj-art-9011e7f13218404eb20a273b438dff5a |
| institution | Kabale University |
| issn | 0717-5000 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Centro Latinoamericano de Estudios en Informática |
| record_format | Article |
| series | CLEI Electronic Journal |
| spelling | doaj-art-9011e7f13218404eb20a273b438dff5a2025-02-06T16:59:25ZengCentro Latinoamericano de Estudios en InformáticaCLEI Electronic Journal0717-50002025-02-0128110.19153/cleiej.28.1.2A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0Maria Amelia Eliseo0Leonildo Carnevalli Junior1Ismar Frango Silveira2Mackenzie Presbyterian UniversityUniversidade Presbiteriana MackenzieUniversidade Presbiteriana Mackenzie Industry 4.0 is driving significant transformations, even in complex and uncertain industrial environments. This concept represents an innovation strategy aimed at redefining the manufacturing sector, enhancing global competitiveness through cost reduction, more agile processes, and superior product quality. Concurrently, Artificial Intelligence (AI) is at the forefront of a profound shift in organizational management and operations, reshaping professional routines and redefining society's interaction with technology. The increasing complexity of business environments, particularly the inherent challenges within industrial sectors, alongside continuous technological advancements, establishes AI as a critical tool not only for fostering innovation but also for optimizing efficiency and enhancing competitiveness across all organizational domains. In this context, this study introduces a structured model grounded in the theoretical exploration of Industry 4.0 maturity models to assess the current maturity levels of AI utilization in the industry. Thus, this work presents the development of a standard for measuring AI adoption levels in Industry 4.0. This index will illuminate companies’ readiness and proficiency in integrating AI into both daily operations and strategic processes. Through the continued application of this tool, companies will also gain insights into their growth across the evaluated domains. https://clei.org/cleiej/index.php/cleiej/article/view/743 |
| spellingShingle | Maria Amelia Eliseo Leonildo Carnevalli Junior Ismar Frango Silveira A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0 CLEI Electronic Journal |
| title | A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0 |
| title_full | A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0 |
| title_fullStr | A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0 |
| title_full_unstemmed | A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0 |
| title_short | A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0 |
| title_sort | comprehensive and structured maturity model for measuring ai adoption levels in industry 4 0 |
| url | https://clei.org/cleiej/index.php/cleiej/article/view/743 |
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