Artificial Intelligence in Ensuring Economically Sustainable Business Development

Against the backdrop of structural transformation in the Russian economy, conventional digitalization approaches fail to deliver long-term economic resilience: companies register short-term operational gains while systemic risks and ESG obligations remain outside the algorithmic decision loop. Aim. The aim of the study is to conceptualize the role of artificial intelligence as a catalyst for sustainable business development and to develop an assessment toolkit for companies’ readiness for AI transformation in the logic of strategic sustainability. Methods. The methodology draws on systemic, comparative and critical-analytical approaches, content analysis of regulatory documents and peer-reviewed publications, and scenario modelling of algorithmic integration into corporate governance. Results : a transition from tactical automation to the formation of predictive, adaptive and ethically verifiable decision-making mechanisms is substantiated; a four-level AI readiness model is proposed, incorporating strategic sustainability, resource efficiency and ESG integration criteria; the ROI sustainability corridor concept is introduced; the BYOA (Bring Your Own Agent) and KCVS (Knowledge Contribution Valuation System) frameworks are considered through the lens of human capital valuation in the AI economy; actionable recommendations for corporate governance and the regulatory environment are formulated. Conclusions. Scientific novelty: AI assets are reconceptualized through the lens of long-term sustainability rather than operational optimization; a criteria framework for sustainabilityoriented digital maturity assessment is developed, accounting for institutional barriers and physical infrastructure; the agent-based approach to knowledge management is substantiated as a factor of organizational economic resilience.

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