Assessing organizational framework conditions for the successful, human-centered introduction of AI applications

Abstract As part of WIRKsam Competence Center, the authors aim to identify and improve organizational conditions in companies that are conducive to the successful introduction of AI technologies in the workplace. This paper examines various factors that are considered crucial for effective AI integration, including technology acceptance, access to IT infrastructure, workforce structure, organizational culture and participatory practices. Using a mixed-methods approach, WIRKsam relates the initial organizational conditions to the researchers’ assessments and experiences of the first 24 months of the study. The analysis uses both qualitative and quantitative data and provides a robust framework for identifying the respective organizational prerequisites. It aims to map these factors and provide insights. Our results show the application partners involved in WIRKsam as companies with individual characteristics of technology and AI affinity as well as different organizational cultures. The workforce is predominantly male. Slightly more than half of the employees are 45 years and older. Overall, the research activities in WIRKsam are met with openness to electronic devices and AI. However, the fears of the employees are somewhat underestimated by the researchers. Employees rate their knowledge and experience with regard to AI as low and need support here in order to be able to participate in the participatory design of work systems in a more informed way. Management support is a key aspect of technology adoption that employees find important. Their absence is accompanied by worries about the job and lower expectations of positive changes in work, among other things. The knowledge gained will be incorporated into the development of tailor-made action plans to optimize conditions in similar environments. Practical relevance: Using the example of the application companies in WIRKsam Competence Center, the results show that there are very different combinations of framework conditions for the successful introduction of AI into operational practice in companies. Action plans can be derived to individually adapt the integrated approach according to the WIRKsam procedure model. The applied mix of methods allows a very comprehensive analysis and contributes to the validity of the results. In particular, the survey of researchers contributes to new findings, the importance of which lies on the one hand in complementing the perspective of employees and the company as a whole, and on the other hand in providing the researchers themselves with a basis for reflecting on their basic assumptions as an entire research team.

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Publication Details

Journal
Zeitschrift für Arbeitswissenschaft
Published
2024-09-01
DOI
https://doi.org/10.1007/s41449-024-00440-7
Citations
2
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
1.06

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article

Assessing organizational framework conditions for the successful, human-centered introduction of AI applications

Markus Harlacher, Andrea Altepost, W. Merx, Farah Elaroussi et al.
2 citations
Zeitschrift für Arbeitswissenschaft
Big Data and Business Intelligence
1.06
article

Assessing organizational framework conditions for the successful, human-centered introduction of AI applications

Markus Harlacher, Andrea Altepost, W. Merx, Farah Elaroussi, Adjan Hansen-Ampah
article en
2 citations

Abstract

Abstract As part of WIRKsam Competence Center, the authors aim to identify and improve organizational conditions in companies that are conducive to the successful introduction of AI technologies in the workplace. This paper examines various factors that are considered crucial for effective AI integration, including technology acceptance, access to IT infrastructure, workforce structure, organizational culture and participatory practices. Using a mixed-methods approach, WIRKsam relates the initial organizational conditions to the researchers’ assessments and experiences of the first 24 months of the study. The analysis uses both qualitative and quantitative data and provides a robust framework for identifying the respective organizational prerequisites. It aims to map these factors and provide insights. Our results show the application partners involved in WIRKsam as companies with individual characteristics of technology and AI affinity as well as different organizational cultures. The workforce is predominantly male. Slightly more than half of the employees are 45 years and older. Overall, the research activities in WIRKsam are met with openness to electronic devices and AI. However, the fears of the employees are somewhat underestimated by the researchers. Employees rate their knowledge and experience with regard to AI as low and need support here in order to be able to participate in the participatory design of work systems in a more informed way. Management support is a key aspect of technology adoption that employees find important. Their absence is accompanied by worries about the job and lower expectations of positive changes in work, among other things. The knowledge gained will be incorporated into the development of tailor-made action plans to optimize conditions in similar environments. Practical relevance: Using the example of the application companies in WIRKsam Competence Center, the results show that there are very different combinations of framework conditions for the successful introduction of AI into operational practice in companies. Action plans can be derived to individually adapt the integrated approach according to the WIRKsam procedure model. The applied mix of methods allows a very comprehensive analysis and contributes to the validity of the results. In particular, the survey of researchers contributes to new findings, the importance of which lies on the one hand in complementing the perspective of employees and the company as a whole, and on the other hand in providing the researchers themselves with a basis for reflecting on their basic assumptions as an entire research team.

Zeitschrift für ArbeitswissenschaftVol. 78(3)
Institut für angewandte Arbeitswissenschaft (DE), FEG Textiltechnik (Germany) (DE)
RWTH Aachen University
Openalex Percentile: Top 17%
Big Data and Business Intelligence
1.06
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