This study provides a comprehensive analysis of the AI-related skills and roles needed to bridge the AI skills gap in Europe. Using a mixed-method research approach, this study investigated the most in-demand AI expertise areas and roles by surveying 409 organizations in Europe, analyzing 2,563 AI-related job advertisements, and conducting 24 focus group sessions with 145 industry and policy experts. The findings underscore the importance of both general technical skills in AI related to big data, machine learning and deep learning, cyber and data security, large language models as well as AI soft skills such as problemsolving and effective communication. This study sets the foundation for future research directions, emphasizing the importance of upskilling initiatives and the evolving nature of AI skills demand, contributing to an EU-wide strategy for future AI skills development.
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Over the past forty years, the use of process models in practice has grown extensively. Until twenty years ago, remarkably little was known about the factors that contribute to the human understandability of process models in practice. Since then, research has, indeed, been conducted on this important topic, by e.g. creating guidelines. Unfortunately, the suggested modelling guidelines often fail to achieve the desired effects, because they are not tied to actual experimental findings. The need arises for knowledge on what kind of visualisation of process models is perceived as understandable, in order to improve the understanding of different stakeholders. Therefore the objective of this study is to answer the question: How can process models be visually enhanced so that they facilitate a common understanding by different stakeholders? Consequently, five subresearch questions (SRQ) will be discussed, covering three studies. By combining social psychology and process models we can work towards a more human-centred and empirical-based solution to enhance the understanding of process models by the different stakeholders with visualisation.
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Due to the changing technological possibilities of services, the demands that society places on the level of service provided by the Dutch Central Government (DCG) are changing rapidly. To accommodate this, the Dutch government is improving its processes in such a way that they become more agile and are continuously improved. However, the DCG struggles with the implementation of improvement tools that can support this. The research described in this paper aims to deliver key factors that influence the adoption of tools that improve the agile way of working and continuous improvement at the DCG. Therefore, a literature review has been conducted, from which 24 factors have been derived. Subsequently, 9 semi structured interviews have been conducted to emphasize the perspective of employees at the DCG. In total, 7 key factors have been derived from the interviews. The interviewees consisted of both employees from departments who already worked with tools to improve agile working and continuous improvement as well as employees from departments who haven’t used such tools yet. An important insight based on this research is that the aims, way of working and scope of the improvement tools must be clear for all the involved co-workers
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