Title: The interaction between humans and machines: A case study on employee job satisfaction during the implementation of artificial intelligence in the workplace Background & problem discussion: As companies adopt new technologies, ensuring job satisfaction is a key for smooth transitions. AI revolutionizes work methods by automating tasks, enhancing efficiency, and requiring new skills. However, AI integration raises concerns about its impacts on roles and satisfaction. While boosting productivity and efficiency, AI can displace human tasks, causing fear and resistance to the new technology. Balancing efficiency with maintaining human expertise is vital, as it affects motivation and engagement in the work. Understanding AI’s impact on job satisfaction is essential, as it significantly influences employees overall experience. Purpose: The purpose of the study is to create an understanding of the employees’ job satisfaction when implementing AI technology in the workplace. Method: This study uses a qualitative research method to understand how AI implementation affects employee job satisfaction at Scania in Oskarshamn. The method focuses on gaining in-depth insights from the employees’ perspective through semi-structured interviews and observations. A case study design was chosen to analyze detailed aspects of AI use within the company. To ensure the reliability, trustworthiness and confirmation of the study, a transparent research process was followed with feedback to the participants. Findings & conclusion: The results showed that both intrinsic and extrinsic involvement were important for job satisfaction. Employees with strategic roles saw AI as an opportunity for improvement, while operational employees felt secure in the use of AI. The study emphasized the importance of fostering an inclusive work culture to ensure positive attitudes towards change and sustained job satisfaction. The conclusion provides both a practical and theoretical contribution for understanding job satisfaction when using AI-technology.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-130343 |
Date | January 2024 |
Creators | Karpö Gustafsson, Ellen, Yaghi, Julia |
Publisher | Linnéuniversitetet, Institutionen för management (MAN) |
Source Sets | DiVA Archive at Upsalla University |
Language | Swedish |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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