Towards AI Governance in DAX40: A Typology of Organizational Guidelines for Self-Regulation

Inhaltsverzeichnis

Bibliographische Infos

Cover der Ausgabe: Swiss Journal of Business Jahrgang 80 (2026), Heft 1
Open Access Vollzugriff

Swiss Journal of Business

Jahrgang 80 (2026), Heft 1

Autor:innen:
Verlag
Nomos, Baden-Baden
Copyrightjahr
2026
ISSN-Online
2944-3741
ISSN-Print
2944-3741

Kapitelinformationen

Open Access Vollzugriff

Jahrgang 80 (2026), Heft 1

Towards AI Governance in DAX40: A Typology of Organizational Guidelines for Self-Regulation

Autor:innen:
ISSN-Print
2944-3741
ISSN-Online
2944-3741
Kapitelvorschau:

In diesem Beitrag verbinden wir den Diskurs zu ethischen Herausforderungen des Einsatzes von Künstlicher Intelligenz (KI) mit Forschungsperspektiven auf eine übergeordnete KI-Governance. Obgleich diese noch nicht institutionalisiert ist, formulieren immer mehr Organisationen eigene Richtlinien für den verantwortungsvollen Einsatz von KI. Diese Selbstregulierungsansätze dienen der Orientierung für Kunden und Beschäftigte. Zugleich dienen sie der Ausrichtung organisatorischer Prozesse und Prüfmechanismen. Wenig bekannt ist, welche Unterschiede es zwischen Selbstregulierungsansätzen gibt und welche zukünftige Ausrichtung einer KI-Governance Organisationen damit antizipieren. Am Beispiel von DAX40-Unternehmen untersuchen wir, wie Organisationen KI-Richtlinien zur Selbstregulierung gestalten und welche Kriterien der KI-Ethik sie dabei berücksichtigen. Auf der Grundlage einer systematischen Suchstrategie und einer qualitativen Inhaltsanalyse identifizieren wir drei verschiedene Typen der Selbstregulierung: (1) nicht kodifizierte Selbstregulierung, (2) symbolisch-technische Selbstregulierung und (3) umfassende sozio-technische Selbstregulierung.

Literaturverzeichnis

  1. Agarwal, A., & Nene, M. J. (2025). A five-layer framework for AI governance: Integrating regulation, standards, and certification. Transforming Government: People, Process and Policy, 19(3), 535–555. https://doi.org/10.1108/TG-03-2025-0065 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  2. Alanoca, S., Gur-Arieh, S., Zick, T., & Klyman, K. (2025). Comparing Apples to Oranges: A Taxonomy for Navigating the Global Landscape of AI Regulation. Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency, 914–937. https://doi.org/10.1145/3715275.3732059 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  3. Attard-Frost, B., & Walters, D. R. (o. J.). The Ethics of AI Business Practices: A Review of 47 AI Ethics Guidelines. AI Ethics 3, 389–406 (2023). https://doi.org/10.1007/s43681-022-00156-6 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  4. Bankins, S., & Formosa, P. (2023). The Ethical Implications of Artificial Intelligence (AI) For Meaningful Work. Journal of Business Ethics, 185(4), 725–740. https://doi.org/10.1007/s10551-023-05339-7 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  5. Batool, A., Zowghi, D., & Bano, M. (2025). AI governance: A systematic literature review. AI and Ethics. https://doi.org/10.1007/s43681-024-00653-w Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  6. Berretta, S., Tausch, A., Ontrup, G., Gilles, B., Peifer, C., & Kluge, A. (2023). Defining human-AI teaming the human-centered way: A scoping review and network analysis. Frontiers in Artificial Intelligence, 6, 1250725. https://doi.org/10.3389/frai.2023.1250725 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  7. Birkstedt, T., Minkkinen, M., Tandon, A., & Mäntymäki, M. (2023). AI governance: Themes, knowledge gaps and future agendas. Internet Research, 33(7), 133–167. https://doi.org/10.1108/INTR-01-2022-0042 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  8. Brynjolfsson, E., Li, D., & Raymond, L. (2025). Generative AI at Work. The Quarterly Journal of Economics, 140(2), 889–942. https://doi.org/10.1093/qje/qjae044 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  9. Cabiddu, F., Lauro, S. D., Samaan, D., & Tursunbayeva, A. (o. J.). Governing AI in the World of Work: An International Review of 245 Ethics Guidelines. Available at SSRN. http://dx.doi.org/10.2139/ssrn.5397353 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  10. Camilleri, M. A. (2024). Artificial intelligence governance: Ethical considerations and implications for social responsibility. Expert Systems, 41(7), Article 7. https://doi.org/10.1111/exsy.13406 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  11. Corrêa, N. K., Galvão, C., Santos, J. W., Del Pino, C., Pinto, E. P., Barbosa, C., Massmann, D., Mambrini, R., Galvão, L., Terem, E., & De Oliveira, N. (2023). Worldwide AI ethics: A review of 200 guidelines and recommendations for AI governance. Patterns, 4(10), 100857. https://doi.org/10.1016/j.patter.2023.100857 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  12. Di Vito, J., & Trottier, K. (2022). A Literature Review on Corporate Governance Mechanisms: Past, Present, and Future*. Accounting Perspectives, 21(2), 207–235. https://doi.org/10.1111/1911-3838.12279 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  13. European Partliament (2024). Artificial Intelligence Act (Regulation (EU), 2024/1689) Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  14. Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  15. Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines, 30(1), Article 1. https://doi.org/10.1007/s11023-020-09517-8 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  16. Herrmann, T., & Pfeiffer, S. (2023). Keeping the organization in the loop: A socio-technical extension of human-centered artificial intelligence. AI & SOCIETY, 38(4), 1523–1542. https://doi.org/10.1007/s00146-022-01391-5 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  17. Hickman, E., & Petrin, M. (2021). Trustworthy AI and Corporate Governance: The EU’s Ethics Guidelines for Trustworthy Artificial Intelligence from a Company Law Perspective. European Business Organization Law Review, 22(4), Article 4. https://doi.org/10.1007/s40804-021-00224-0 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  18. Hickok, M. (2021). Lessons learned from AI ethics principles for future actions. AI and Ethics, 1(1), Article 1. https://doi.org/10.1007/s43681-020-00008-1 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  19. Jarzabkowski, P., & Paul Spee, A. (2009). Strategy‐as‐practice: A review and future directions for the field. International Journal of Management Reviews, 11(1), 69–95. https://doi.org/10.1111/j.1468-2370.2008.00250.x Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  20. Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), Article 9. https://doi.org/10.1038/s42256-019-0088-2 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  21. Leonardi, P. M., & Treem, J. W. (2020). Behavioral Visibility: A new paradigm for organization studies in the age of digitization, digitalization, and datafication. Organization Studies, 41(12), 1601–1625. https://doi.org/10.1177/0170840620970728 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  22. Lombard, M., Snyder-Duch, J., & Bracken, C. C. (2002). Content Analysis in Mass Communication: Assessment and Reporting of Intercoder Reliability. Human Communication Research, 28(4), 587–604. https://doi.org/10.1111/j.1468-2958.2002.tb00826.x Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  23. Maman, L., & Feldman, Y. (2025). Compliance and Effectiveness of Industry Self-Regulation: A Systematic Literature Review. Available at SSRN. http://dx.doi.org/10.2139/ssrn.5233166 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  24. Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022a). Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governance (No. arXiv:2206.00335; Nummer arXiv:2206.00335). arXiv. https://doi.org/10.48550/arXiv.2206.00335 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  25. Mäntymäki, M., Minkkinen, M., Birkstedt, T., & Viljanen, M. (2022b). Defining organizational AI governance. AI and Ethics, 2(4), Article 4. https://doi.org/10.1007/s43681-022-00143-x Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  26. Mayring, P., & Fenzl, T. (2014). Qualitative Inhaltsanalyse. In N. Baur & J. Blasius (Eds.), Handbuch Methoden der empirischen Sozialforschung (pp. 543–556). Springer. https://doi.org/10.1007/978-3-531-18939-0_38 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  27. Mayring, P. (2019). Qualitative Inhaltsanalyse – Abgrenzungen, Spielarten, Weiterentwicklungen. Forum Qualitative Social Research, 20(3), 15. https://doi.org/10.17169/fqs-20.3.3343 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  28. Meske, C., Bunde, E., Schneider, J., & Gersch, M. (2022). Explainable Artificial Intelligence: Objectives, Stakeholders, and Future Research Opportunities. Information Systems Management, 39(1), 53–63. https://doi.org/10.1080/10580530.2020.1849465 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  29. Mueller, B. (2022). Corporate Digital Responsibility. Business & Information Systems Engineering, 64(5), 689–700. https://doi.org/10.1007/s12599-022-00760-0 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  30. Nitsch, V., Rick, V., Kluge, A., & Wilkens, U. (2024). Human-centered approaches to AI-assisted work: The future of work? Zeitschrift Für Arbeitswissenschaft, 78(3), 261–267. https://doi.org/10.1007/s41449-024-00437-2 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  31. Orlikowski, W. J., & Scott, S. V. (2008). 10 Sociomateriality: Challenging the Separation of Technology, Work and Organization. Academy of Management Annals, 2(1), 433–474. https://doi.org/10.5465/19416520802211644 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  32. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, n71. https://doi.org/10.1136/bmj.n71 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  33. Papagiannidis, E., Mikalef, P., & Conboy, K. (2025). Responsible artificial intelligence governance: A review and research framework. The Journal of Strategic Information Systems, 34(2), 101885. https://doi.org/10.1016/j.jsis.2024.101885 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  34. Parker, S. K., & Grote, G. (2022). Automation, Algorithms, and Beyond: Why Work Design Matters More Than Ever in a Digital World. Applied Psychology, 71(4), 1171–1204. https://doi.org/10.1111/apps.12241 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  35. Prem, E. (2023). From ethical AI frameworks to tools: A review of approaches. AI and Ethics, 3(3), 699–716. https://doi.org/10.1007/s43681-023-00258-9 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  36. Prem, E. (2024). Approaches to Ethical AI. In H. Werthner, C. Ghezzi, J. Kramer, J. Nida-Rümelin, B. Nuseibeh, E. Prem, & A. Stanger (Hrsg.), Introduction to Digital Humanism (S. 225–239). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-45304-5_15 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  37. Schneider, J., Abraham, R., Meske, C., & Vom Brocke, J. (2023). Artificial Intelligence Governance For Businesses. Information Systems Management, 40(3), Article 3. https://doi.org/10.1080/10580530.2022.2085825 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  38. Schneider, J., Abraham, R., & Meske, C. (2024). Governance of generative artificial intelligence for companies. arXiv preprint arXiv:2403.08802. https://doi.org/10.48550/arXiv.2403.08802 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  39. Seidl, D., Ma, S., & Splitter, V. (2024). What makes activities strategic: Toward a new framework for strategy‐as‐practice research. Strategic Management Journal, 45(12), 2395–2419. https://doi.org/10.1002/smj.3668 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  40. Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  41. Stahl, B. C., Antoniou, J., Ryan, M., Macnish, K., & Jiya, T. (2022). Organisational responses to the ethical issues of artificial intelligence. AI & SOCIETY, 37(1), Article 1. https://doi.org/10.1007/s00146-021-01148-6 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  42. Viljanen, M., & Parviainen, H. (2022). AI Applications and Regulation: Mapping the Regulatory Strata. Frontiers in Computer Science, 3, 779957. https://doi.org/10.3389/fcomp.2021.779957 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  43. Von Krogh, G. (2018). Artificial Intelligence in Organizations: New Opportunities for Phenomenon-Based Theorizing. Academy of Management Discoveries, 4(4), 404–409. https://doi.org/10.5465/amd.2018.0084 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  44. Whittington, R. (2006). Completing the Practice Turn in Strategy Research. Organization Studies, 27(5), 613–634. https://doi.org/10.1177/0170840606064101 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  45. Widder, D. G., & Nafus, D. (2023). Dislocated accountabilities in the “AI supply chain”: Modularity and developers’ notions of responsibility. Big Data & Society, 10(1), Article 1. https://doi.org/10.1177/20539517231177620 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  46. Wilkens, U., Lupp, D., & Langholf, V. (2023). Configurations of human-centered AI at work: Seven actor-structure engagements in organizations. Frontiers in Artificial Intelligence, 6, 1272159. https://doi.org/10.3389/frai.2023.1272159 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50
  47. Wirtz, B. W., Weyerer, J. C., & Kehl, I. (2022). Governance of artificial intelligence: A risk and guideline-based integrative framework. Government Information Quarterly, 39(4), 101685. https://doi.org/10.1016/j.giq.2022.101685 Google Scholar öffnen DOI: 10.5771/2944-3741-2026-1-50

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