Perception of Automation, AI, and Collaboration in Manufacturing

Abstract This research investigates the perceptions and attitudes towards artificial intelligence (AI) and automation in manufacturing settings. A multimodal data collection approach is used to gather participant responses using surveys, focus group discussions, and interviews. Qualitative and quantitative data collected from six manufacturing companies are analyzed to explore the multifaceted dynamics influencing the adoption and acceptance of AI and automation technologies. The study investigates specific views, concerns, and expectations regarding the implementation of these technologies, shedding light on the nuanced perspectives of participants across different organizational contexts. By examining factors such as personal strategies, sentiment analysis, relevance to roles, and technology acceptance, the research offers insights into the complex interaction between technological advancement, organizational culture, and individual attitudes. Varying levels of understanding regarding technological relevance to roles are observed, alongside concerns about job displacement and decision-making transparency. Participants differ in their belief in AI and automation’s potential to address concerns, highlighting the need for tailored integration strategies. Unique observations, such as machine personalization and cultural influences, are uncovered. Conclusions stress the importance of addressing these complexities in adoption efforts, while future work aims to expand datasets and explore new data collection methods to inform integration strategies. Future work includes analysis of the focus group and interview transcripts for confirmation of these findings.