Designing Effective AI Certification

Insights from established certification domains for the standardization of human-centered AI

JournalIndustry 4.0 Science
Issue Volume 44, 2026, Edition 5, Pages 86-92
Open Access10.30844/I4SE.26.4.8
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Abstract

Certification can institutionalize normative requirements, but the degree to which this is achieved varies considerably. Drawing on expert interviews from established certification domains, this paper identifies indicators and conditions for the effective embedding of standards and transfers these insights to the context of AI. Substantial embedding is not evident in the certification event itself, but rather across audit cycles. Leadership commitment, the role of the internal representative, and practically applicable indicators emerge as key enabling factors. The paper derives three areas of action for the process certification of human-centered AI deployed in workplace processes.

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Article

Certification for human-centered AI is becoming increasingly important—as a source of competitive differentiation, a response to regulatory expectations, and a mechanism for fostering human-centered work environments. But how can organizations determine whether the underlying requirements are truly embedded in practice? Drawing on expert interviews from established certification domains, this paper shows that the decisive question is answered not during the audit itself, but in the period between audit cycles. Ultimately, it is not the certificate that matters, but the commitment of organizational leadership and the organization as a whole to engage seriously in the certification process and its continuous implementation.

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