Igor Kabashkin
The rapid integration of artificial intelligence (AI) into professional, educational, and everyday cognitive processes has created a dual dynamic of cognitive growth and cognitive atrophy. This study introduces a unified theoretical and quantitative framework to analyze these opposing tendencies and their equilibrium, conceptualized as the cognitive co-evolution model. The model interprets human–AI interaction as a nonlinear process in which reflective engagement enhances metacognitive skills, while over-delegation to automation reduces analytical autonomy. To quantify this balance, the paper proposes the cognitive sustainability index (CSI) as a composite measure integrating five behavioral parameters representing autonomy, reflection, creativity, delegation, and reliance. Simulation examples and domain-specific illustrations, including the case of software developers, demonstrate how CSI values can reveal distinct cognitive zones ranging from atrophy to synergy. Building upon these findings, the paper develops the framework of applied cognitive management, which links cognitive monitoring with adaptive interventions across individual, educational, professional, and institutional levels. The results highlight the need for organizations and policymakers to monitor cognitive sustainability as a strategic indicator of digital transformation. Maintaining CSI above the sustainability threshold ensures that automation enhances rather than replaces human reasoning, creativity, and ethical responsibility. The study concludes by outlining methodological challenges and future research directions toward a quantitative science of cognitive sustainability and co-evolutionary human–AI ecosystems.