Responsible AI maturity model in the strategic management of corporate social responsibility of enterprises
DOI:
https://doi.org/10.26565/2786-4995-2026-3-13Keywords:
artificial intelligence, Responsible AI, corporate social responsibility, maturity model, ESG strategies, digital transformation, social impactAbstract
The object of the study is the processes of integrating artificial intelligence (AI) into the strategic management of corporate social responsibility (CSR) of enterprises amidst digital transformation, the spread of ESG approaches, and rising ethical challenges, particularly in unstable and wartime conditions.
Problem Statement. Modern enterprises are actively implementing AI technologies, necessitating their alignment with social, environmental, and ethical responsibility principles. At the same time, existing management approaches are fragmented: technological aspects of AI are considered separately from CSR concepts, creating a methodological gap between digitalization and strategic CSR management. This complicates transparency, accountability, and the ethics of AI use, while limiting the potential for long-term competitive advantages.
Unresolved aspects of the problem. Comprehensive approaches to forming models that integrate AI maturity levels, Responsible AI principles, quantitative efficiency evaluation systems, and adaptive feedback mechanisms remain underdeveloped, especially under high uncertainty.
Purpose of the аrticle. The study aims to theoretically substantiate and develop a Responsible AI maturity model within the strategic CSR management system, establish approaches for evaluating its effectiveness based on Key Performance Indicators (KPIs), and develop practical implementation recommendations.
Presentation of the main material. The article proposes an original AI integration maturity model featuring five development levels (from reactive to transformational), a built-in Responsible AI ethical control mechanism, a Key Performance Indicator system (ІCSR, AAI, MESG, Sindex), and a cyclic implementation algorithm. Methods used include systems analysis, modeling, comparative analysis, and quantitative assessment. The model was tested on enterprises of various scales.
Conclusions. The developed model provides comprehensive, adaptive, and ethically oriented AI integration into CSR management, enhancing decision-making efficiency and transparency. It serves as a tool for strategic planning and Responsible AI maturity diagnostics.
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