UDC 658.51
DOI: 10.36871/ek.up.p.r.2026.04.14.006

Authors

Margarita V. Medvedeva,
St. Petersburg State Electrotechnical University “LETI” named after V. I. Ulyanov (Lenin), St. Petersburg, Russia

Abstract

In the context of the digital economy and the widespread deployment of artificial intelligence (AI) algorithms for diverse tasks within quality management systems (QMS), a fundamentally new challenge has emerged: traditional quality assessment models, oriented toward compliance and process stability, fail to ensure control over the cognitive mechanisms of managerial decision-making. The purpose of this study is to develop a cognitive goal metamodel for assessing quality management systems based on the integration of the Quality 4.0 concept and the DIKWP philosophy, enabling the formalization of the human control zone over automatically generated decisions. The study employs methods of structuralfunctional analysis, comparative analysis of quality architectures, a systems approach to standardization, and formalization of cognitive processes. An operational definition of “quality” in the context of managerial decision-making is proposed as a meta-category encompassing three criteria: semantic correctness, strategic appropriateness, and ethical consistency. The integration of DIKWP with the requirements of GOST R ISO 9001-2015 is systematized by specific sections of the standard, and measurable cognitive metrics are developed for the QMS maturity self-assessment tool in accordance with GOST R ISO 9004- 2019.<br>

Keywords

artificial intelligence (AI) systems, quality management system, DIKWP model, Quality 4.0, cognitive maturity, semantic correctness, standardization

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