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<p>This paper argues that internal AI guidelines can serve as a&#xa0;practical, participatory instrument for responsible AI adoption in organizations. Building on the work of the project <i>Zukunftszentrum KI NRW</i>, it presents and tests a&#xa0;three-part workshop concept with five companies in North Rhine-Westphalia that combines AI literacy, value clarification, and use case-based analysis with the involvement of diverse stakeholders (e.g. works councils, managers, employees). The exploratory qualitative findings identify central values (including human-centricity, data privacy, transparency, fairness, and responsibility) and key challenges (especially people and change management, data protection, result quality and control, and qualification). They also show that participatory guideline processes can make governance-related implementation needs visible when abstract responsible AI principles are translated into company-specific rules and routines. The paper thus offers both conceptual orientation and practice-oriented guidance for operationalising responsible AI in organizations.</p>

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AI guidelines for companies

  • 期刊论文

  • 发表日期：

    2026年4月13日

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  • Bianca Zickerick

摘要

This paper argues that internal AI guidelines can serve as a practical, participatory instrument for responsible AI adoption in organizations. Building on the work of the project Zukunftszentrum KI NRW, it presents and tests a three-part workshop concept with five companies in North Rhine-Westphalia that combines AI literacy, value clarification, and use case-based analysis with the involvement of diverse stakeholders (e.g. works councils, managers, employees). The exploratory qualitative findings identify central values (including human-centricity, data privacy, transparency, fairness, and responsibility) and key challenges (especially people and change management, data protection, result quality and control, and qualification). They also show that participatory guideline processes can make governance-related implementation needs visible when abstract responsible AI principles are translated into company-specific rules and routines. The paper thus offers both conceptual orientation and practice-oriented guidance for operationalising responsible AI in organizations.