Bunzel, NiklasGöller, NicolasKlein, MaikeKrupka, DanielWinter, CorneliaGergeleit, MartinMartin, Ludger2024-10-212024-10-212024978-3-88579-746-32944-7682https://dl.gi.de/handle/20.500.12116/45158In the rapidly evolving landscape of artificial intelligence (AI), the challenge of establishing a unified framework for AI regularization and standardization is increasingly critical. Standardization organizations worldwide, while striving to create guidelines for trustworthy AI, often diverge in their approaches and terminologies. This divergence leads to significant challenges for legislators in enacting comprehensive laws, such as the EU AI Act, and poses even greater challenges for companies expected to comply with these laws and diverse standards. Amidst this complexity, the Open Worldwide Application Security Project (OWASP) AI Exchange emerges as a pivotal solution. This initiative seeks to harmonize AI security standards and practices, thereby providing a much-needed bridge between varying regulatory expectations and practical implementation strategies for AI. This research paper delves into the role of the OWASP AI Exchange in simplifying and standardizing the realm of trustworthy AI, providing a cohesive framework that benefits legislators, industries, and the broader AI community.enArtificial IntelligenceRegularization of AITrustworthy AIStandardization of AIText/Conference Paper10.18420/inf2024_181617-54682944-7682