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.

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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
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article

Who Matters in AI Compliance? A Stakeholder Framework for Enterprise Strategies

Michael H. Breitner, Leonard Kost, Samantha Webster
ScholarSpace (University of Hawaii at Manoa)
Ethics and Social Impacts of AI
article

Who Matters in AI Compliance? A Stakeholder Framework for Enterprise Strategies

Michael H. Breitner, Leonard Kost, Samantha Webster
article en

Abstract

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.

ScholarSpace (University of Hawaii at Manoa)
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Openalex Percentile: Top 27%
Ethics and Social Impacts of AI
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