Multiplier case: Generative AI at SEEPEX<\/h2><\/div>Monitoring and evaluation of user behaviour during the introduction of generative AI<\/h4><\/div><\/div><\/div><\/div><\/div>Summary<\/h3><\/div><\/div><\/div>In this sub-project, the roll-out of the generative AI tool Microsoft Copilot at SEEPEX is being scientifically monitored and evaluated with a view to developing a process model for the roll-out of generative AI tools in organisations. In collaboration with the IAW, user behaviour is being analysed and implications for supporting measures \u2013 such as training programmes \u2013 are being derived from this analysis.<\/p>\n<\/div><\/div><\/div>
![](\"https:\/\/humaine.info\/wp-content\/uploads\/2025\/04\/IMG_20250212_131309-scaled.jpg\" "\\"IMG_20250212_131309\\"")
<\/span><\/div><\/div><\/div>Description of the Approach<\/h3><\/div>First, an understanding of the context is established in order to grasp the various aspects of the onboarding process. The methodological approach for the subsequent study is derived from this. The study will take the form of user interviews conducted at two different points in time. The first interviews will provide a \u2018status quo analysis\u2019 of the orientation phase. This will be followed by a second round of interviews. This approach will enable user behaviour to be examined over time.<\/p>\n<\/div><\/div><\/div>
Goals & Results<\/h3><\/div>The sub-project aims to analyse user behaviour, examine qualitative aspects such as acceptance of and trust in the AI tool, and thereby identify any need for adjustments to the training programme and other supporting measures implemented by the company.<\/p>\n<\/div><\/div><\/div>
<\/i><\/i><\/span>Scientific Publications<\/span><\/a><\/h4><\/div>\nObermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Partner<\/h1><\/div><\/div><\/div>Practice Partners<\/h3><\/div>
Monitoring and evaluation of user behaviour during the introduction of generative AI<\/h4><\/div><\/div><\/div><\/div><\/div>Summary<\/h3><\/div><\/div><\/div>In this sub-project, the roll-out of the generative AI tool Microsoft Copilot at SEEPEX is being scientifically monitored and evaluated with a view to developing a process model for the roll-out of generative AI tools in organisations. In collaboration with the IAW, user behaviour is being analysed and implications for supporting measures \u2013 such as training programmes \u2013 are being derived from this analysis.<\/p>\n<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Description of the Approach<\/h3><\/div>First, an understanding of the context is established in order to grasp the various aspects of the onboarding process. The methodological approach for the subsequent study is derived from this. The study will take the form of user interviews conducted at two different points in time. The first interviews will provide a \u2018status quo analysis\u2019 of the orientation phase. This will be followed by a second round of interviews. This approach will enable user behaviour to be examined over time.<\/p>\n<\/div><\/div><\/div>
Goals & Results<\/h3><\/div>The sub-project aims to analyse user behaviour, examine qualitative aspects such as acceptance of and trust in the AI tool, and thereby identify any need for adjustments to the training programme and other supporting measures implemented by the company.<\/p>\n<\/div><\/div><\/div>
<\/i><\/i><\/span>Scientific Publications<\/span><\/a><\/h4><\/div>\nObermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Partner<\/h1><\/div><\/div><\/div>Practice Partners<\/h3><\/div>
Summary<\/h3><\/div><\/div><\/div>In this sub-project, the roll-out of the generative AI tool Microsoft Copilot at SEEPEX is being scientifically monitored and evaluated with a view to developing a process model for the roll-out of generative AI tools in organisations. In collaboration with the IAW, user behaviour is being analysed and implications for supporting measures \u2013 such as training programmes \u2013 are being derived from this analysis.<\/p>\n<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Description of the Approach<\/h3><\/div>First, an understanding of the context is established in order to grasp the various aspects of the onboarding process. The methodological approach for the subsequent study is derived from this. The study will take the form of user interviews conducted at two different points in time. The first interviews will provide a \u2018status quo analysis\u2019 of the orientation phase. This will be followed by a second round of interviews. This approach will enable user behaviour to be examined over time.<\/p>\n<\/div><\/div><\/div>
Goals & Results<\/h3><\/div>The sub-project aims to analyse user behaviour, examine qualitative aspects such as acceptance of and trust in the AI tool, and thereby identify any need for adjustments to the training programme and other supporting measures implemented by the company.<\/p>\n<\/div><\/div><\/div>
<\/i><\/i><\/span>Scientific Publications<\/span><\/a><\/h4><\/div>\nObermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Partner<\/h1><\/div><\/div><\/div>Practice Partners<\/h3><\/div>
In this sub-project, the roll-out of the generative AI tool Microsoft Copilot at SEEPEX is being scientifically monitored and evaluated with a view to developing a process model for the roll-out of generative AI tools in organisations. In collaboration with the IAW, user behaviour is being analysed and implications for supporting measures \u2013 such as training programmes \u2013 are being derived from this analysis.<\/p>\n<\/div><\/div><\/div>
<\/span><\/div><\/div><\/div>Description of the Approach<\/h3><\/div>First, an understanding of the context is established in order to grasp the various aspects of the onboarding process. The methodological approach for the subsequent study is derived from this. The study will take the form of user interviews conducted at two different points in time. The first interviews will provide a \u2018status quo analysis\u2019 of the orientation phase. This will be followed by a second round of interviews. This approach will enable user behaviour to be examined over time.<\/p>\n<\/div><\/div><\/div>
Goals & Results<\/h3><\/div>The sub-project aims to analyse user behaviour, examine qualitative aspects such as acceptance of and trust in the AI tool, and thereby identify any need for adjustments to the training programme and other supporting measures implemented by the company.<\/p>\n<\/div><\/div><\/div>
<\/i><\/i><\/span>Scientific Publications<\/span><\/a><\/h4><\/div>\nObermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Partner<\/h1><\/div><\/div><\/div>Practice Partners<\/h3><\/div>
First, an understanding of the context is established in order to grasp the various aspects of the onboarding process. The methodological approach for the subsequent study is derived from this. The study will take the form of user interviews conducted at two different points in time. The first interviews will provide a \u2018status quo analysis\u2019 of the orientation phase. This will be followed by a second round of interviews. This approach will enable user behaviour to be examined over time.<\/p>\n<\/div><\/div><\/div>
Goals & Results<\/h3><\/div>The sub-project aims to analyse user behaviour, examine qualitative aspects such as acceptance of and trust in the AI tool, and thereby identify any need for adjustments to the training programme and other supporting measures implemented by the company.<\/p>\n<\/div><\/div><\/div>
<\/i><\/i><\/span>Scientific Publications<\/span><\/a><\/h4><\/div>\nObermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Partner<\/h1><\/div><\/div><\/div>Practice Partners<\/h3><\/div>
The sub-project aims to analyse user behaviour, examine qualitative aspects such as acceptance of and trust in the AI tool, and thereby identify any need for adjustments to the training programme and other supporting measures implemented by the company.<\/p>\n<\/div><\/div><\/div>
<\/i><\/i><\/span>Scientific Publications<\/span><\/a><\/h4><\/div>\nObermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
Partner<\/h1><\/div><\/div><\/div>Practice Partners<\/h3><\/div>
Obermann, N., Lupp, D., & Wilkens, U. (2025). Mechanisms of GenAI governance: A case study on the responsible use of GenAI in organizations. Industry 4.0 Science.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/div>
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