Who Matters in AI Compliance? A Stakeholder Framework for Enterprise Strategies
As artificial intelligence (AI) becomes central to enterprise operations, aligning AI strategies with regulatory developments is increasingly vital. This study proposes a stakeholder-involved maturity model to embed AI compliance into organizational processes. Design Science Research-oriented, the maturity model integrates findings from literature, expert interviews, a focus group discussion, and an evaluative single case study. Including a four-staged maturity assessment, 12 relevant stakeholders with specific responsibilities are identified to address AI regulation in enterprise AI strategies. Results show varying stakeholder relevance across maturity levels and highlight the importance of cross-functional collaboration across crucial department units. The model offers a triangulation of insights in a structured management framework. Based on a comprehensive stakeholder analysis and a consequential involvement intensity for AI regulation integration in enterprises, we develop and contribute to research by providing a structured and actionable framework for organizations aiming to implement and transition to increased AI compliance.
Authors
- Michael H. Breitner (ORCID: https://orcid.org/0000-0001-7315-3022)
- Leonard Kost (ORCID: https://orcid.org/0009-0004-0072-9835)
- Samantha Webster
Publication Details
- Journal
- ScholarSpace (University of Hawaii at Manoa)
- Published
- 2025-12-23
- Primary Topic
- Ethics and Social Impacts of AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00