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<p>AI agents can enable highly scalable processing of heterogeneous datasets in data management, reduce manual effort, and thereby provide the foundation for faster, more robust, and more transparent data-driven decision-making. Against the backdrop of skills shortages and increasing compliance requirements, agentic systems act as a&#xa0;lever to shift limited human resources toward complex, value-adding tasks while simultaneously improving governance, transparency, and quality standards of data assets. At the same time, the deployment of AI agents fundamentally transforms the socio-technical work system of data management, particularly with regard to employees’ degrees of autonomy and required competencies. This paper examines the future impact of AI agents on the socio-technical work system of data management in the domain of intelligent mobility and analyzes the resulting changes. The transformation is assessed along the four dimensions of socio-technical systems: technology, people, tasks, and structure. The findings indicate that AI agents primarily automate repetitive routine activities, while human work increasingly focuses on complex and value-creating tasks. New role profiles and ideal types of data workers are emerging: alongside AI bureaucrats, who ensure adherence to policies and compliance requirements, AI entrepreneurs are gaining importance by leveraging exploratory uses of AI to develop innovative solutions. Furthermore, a&#xa0;growing need for more centralized organizational structures to govern and take responsibility for AI deployment is becoming apparent. For practitioners in the field of intelligent mobility, this study identifies key areas of transformation in data management and supports a&#xa0;proactive approach to shaping the forthcoming transition.</p>

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Einflüsse von agentischer KI auf das Datenmanagement: Eine soziotechnische Analyse im Bereich der intelligenten Mobilität

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月30日

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  • Nils Jahnke,
  • Sarah Schimankowitz,
  • Maik Mannsfeld

摘要

AI agents can enable highly scalable processing of heterogeneous datasets in data management, reduce manual effort, and thereby provide the foundation for faster, more robust, and more transparent data-driven decision-making. Against the backdrop of skills shortages and increasing compliance requirements, agentic systems act as a lever to shift limited human resources toward complex, value-adding tasks while simultaneously improving governance, transparency, and quality standards of data assets. At the same time, the deployment of AI agents fundamentally transforms the socio-technical work system of data management, particularly with regard to employees’ degrees of autonomy and required competencies. This paper examines the future impact of AI agents on the socio-technical work system of data management in the domain of intelligent mobility and analyzes the resulting changes. The transformation is assessed along the four dimensions of socio-technical systems: technology, people, tasks, and structure. The findings indicate that AI agents primarily automate repetitive routine activities, while human work increasingly focuses on complex and value-creating tasks. New role profiles and ideal types of data workers are emerging: alongside AI bureaucrats, who ensure adherence to policies and compliance requirements, AI entrepreneurs are gaining importance by leveraging exploratory uses of AI to develop innovative solutions. Furthermore, a growing need for more centralized organizational structures to govern and take responsibility for AI deployment is becoming apparent. For practitioners in the field of intelligent mobility, this study identifies key areas of transformation in data management and supports a proactive approach to shaping the forthcoming transition.