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AI-Governed Intelligent Maturity Management of Industrial Ecosystems in Industry 6.0
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This paper introduces a conceptual, architectural, and empirical framework for artificial intelligence (AI)-governed management of intelligent maturity in industrial ecosystems within the emerging paradigm of Industry 6.0. The study redefines the maturity concept, shifting from digital maturity – understood as the degree of technological integration – to intelligent maturity, interpreted as the capability of distributed systems to learn, adapt, and self-organize through human–AI co-evolution. Unlike existing digital maturity and AI readiness models, the proposed framework conceptualizes intelligent maturity as an integrated governance capability emerging from the interaction of technological, cognitive, organizational, and ecosystem dimensions. The analysis focuses on the national industrial ecosystem of the Russian Federation, comprising three core sectors: mining, manufacturing, and electricity, gas, and steam supply (including air conditioning). Empirical evaluation based on Rosstat data (2021–2023) demonstrates a steady growth of the Intelligent Maturity Index from 0.39 to 0.46, with the most dynamic increase observed in manufacturing (+0.07 points). This indicates a progressive transition of the industrial system from digital to intelligent maturity, reflected in increasing AI adoption, innovation activity, and adaptive capacity. A distributed cognitive architecture is proposed, comprising technological, cognitive, organizational, and ecosystem layers interconnected by AI-enabled feedback loops. Within this framework, AI functions as a co-governing cognitive agent, enabling reflexive decision-making, semantic interoperability, and predictive adaptation across distributed industrial networks. The research contributes to the theory and practice of intelligent management by positioning intelligent maturity as a measurable and actionable meta-category of Industry 6.0 governance that integrates technology, cognition, and ethics into a unified adaptive system.
Title: AI-Governed Intelligent Maturity Management of Industrial Ecosystems in Industry 6.0
Description:
This paper introduces a conceptual, architectural, and empirical framework for artificial intelligence (AI)-governed management of intelligent maturity in industrial ecosystems within the emerging paradigm of Industry 6.
The study redefines the maturity concept, shifting from digital maturity – understood as the degree of technological integration – to intelligent maturity, interpreted as the capability of distributed systems to learn, adapt, and self-organize through human–AI co-evolution.
Unlike existing digital maturity and AI readiness models, the proposed framework conceptualizes intelligent maturity as an integrated governance capability emerging from the interaction of technological, cognitive, organizational, and ecosystem dimensions.
The analysis focuses on the national industrial ecosystem of the Russian Federation, comprising three core sectors: mining, manufacturing, and electricity, gas, and steam supply (including air conditioning).
Empirical evaluation based on Rosstat data (2021–2023) demonstrates a steady growth of the Intelligent Maturity Index from 0.
39 to 0.
46, with the most dynamic increase observed in manufacturing (+0.
07 points).
This indicates a progressive transition of the industrial system from digital to intelligent maturity, reflected in increasing AI adoption, innovation activity, and adaptive capacity.
A distributed cognitive architecture is proposed, comprising technological, cognitive, organizational, and ecosystem layers interconnected by AI-enabled feedback loops.
Within this framework, AI functions as a co-governing cognitive agent, enabling reflexive decision-making, semantic interoperability, and predictive adaptation across distributed industrial networks.
The research contributes to the theory and practice of intelligent management by positioning intelligent maturity as a measurable and actionable meta-category of Industry 6.
0 governance that integrates technology, cognition, and ethics into a unified adaptive system.
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