AI Act in BPMN: More Than Just Words—A Perspective for Providers of AI Systems

Abstract

This article presents a practical and visual Business Process Modeling and Notation (BPMN)-based guide to support the assessment of artificial intelligence (AI) systems under the EU AI Act, with the aim of identifying their risk classification and the corresponding compliance obligations. The proposed approach structures the assessment process as a guided decision-making pathway, composed of a sequence of questions derived from the regulatory framework. Through this step-by-step process, providers of AI systems can systematically determine whether their AI systems fall within prohibited, high-risk, limited-risk, or minimal-risk categories and identify the applicable sets of obligations. The use of BPMN enables a transparent and intuitive representation of the assessment logic, making the methodology accessible to a wide range of AI systems' providers, including those without legal expertise. At the same time, it ensures traceability of each decision point and facilitates the identification of critical elements within the compliance process. A key feature of the proposed framework is its adaptability: the BPMN structure can be easily updated as new guidelines, technical standards, and implementing measures are issued under the AI Act. Furthermore, the methodology has been developed within an institutional setting, specifically the AI Factory IT4LIA, and the EuSAiR project, ensuring alignment with ongoing regulatory developments and practical relevance for real-world applications.

Received: 23 March 2026 | Revised: 22 July 2026 | Accepted: 28 August 2026

Conflicts of Interest

Ilaria Angela Amantea is the Peer Review Board Member for the Journal of Computational Law and Legal Technology and was not involved in the editorial review or the decision to publish this article. The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

The data that support the findings of this study are openly available in the repository at https://github.com/Marinelele/Project-AI-Act-BPMN-/blob/main/Context1.png.

Author Contribution Statement

Marinella Quaranta: Conceptualization, Methodology, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration. Ilaria Angela Amantea: Methodology, Validation, Formal analysis, Investigation, Writing – review & editing, Supervision, Project administration.