Graphical AI workflow modelling: Identifying relevant competencies in AI-based automation of business processes

Abstract: This research investigates how Artificial Intelligence (AI) can be systematically integrated into existing business processes by combining suitable competencies with graphical AI workflow modelling. While AI offers a high potential for automation and increased efficiency, its implementation often fails due to a lack of interdisciplinary competencies that bridge the gap between domain expertise and IT know-how. Low-code platforms and visual modelling tools are increasingly recognised as enablers, empowering non-programmers to intuitively create graphical AI- based workflows. Nevertheless, specific competencies are required to realise the full potential of AI, the domain specific knowledge and align technical understanding with AI capabilities. The paper reviews the state of the art in AI-driven business process automation and competencies for visual low-code approaches. It then presents a practical solution to identify and systematise essential competence areas. Based on this, a practical competence model is developed to support the design of user-friendly, AI-enabled workflows. This is tested in a practical application context — emergency management — where it supports critical decision-making processes and is validated through expert feedback. The study concludes by offering actionable recommendations to help organisations foster the necessary competencies and methods for competently integrating AI into their digital processes.

Keywords: Graphical Workflow, Artificial Intelligence, Business Process, Competence, Skill

DOI: 10.54941/ahfe1006785

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