Company perspectives of generative artificial intelligence in industrial work

The use of artificial intelligence (AI) technologies in the manufacturing industry is rapidly increasing. During this transformation, it can be difficult to understand how AI will change the way work is done. This study explores how generative AI could change manufacturing work. Data collection was...

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Bibliographic Details
Published in:Procedia computer science Vol. 253; pp. 217 - 226
Main Authors: Aromaa, Susanna, Heikkilä, Päivi, Jurvansuu, Marko, Pehlivan, Selen, Väärä, Teijo, Jurmu, Marko
Format: Journal Article
Language:English
Published: Elsevier B.V 2025
Subjects:
company perspective
ergonomics
Generative artificial intelligence
human factors
industry work
manufacturing
manufacturing
company perspective
industry work
Generative artificial intelligence
human factors
ergonomics
ISSN:1877-0509, 1877-0509
Online Access:Get full text
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Summary:The use of artificial intelligence (AI) technologies in the manufacturing industry is rapidly increasing. During this transformation, it can be difficult to understand how AI will change the way work is done. This study explores how generative AI could change manufacturing work. Data collection was conducted using interviews and a questionnaire with seven representatives from three industrial companies. They identified several application areas for GenAI in the industrial work context, such as design, planning, training, problem solving, coding and data management. They also expressed positive attitudes but raised concerns about trust, safety, acceptability and interoperability. Changes in work were identified as being more related to cognitive aspects such as changing the way of thinking and altering the interaction with people and machines. Therefore, human-AI design efforts should focus especially on cognitive ergonomics. Findings from this study can be used in the manufacturing industry when adopting AI, as well as in identifying research topics in the human-AI research community.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2025.01.085