Cognitive Engagement as a Key Mechanism of Cognitive Sustainability in the Age of Generative AI: An Interdisciplinary Framework

Generative Artificial Intelligence (GenAI) systems can improve productivity, yet their long-term implications for human cognition remain contested. This article develops an interdisciplinary framework for explaining how different patterns in the distribution and support of cognitive operations between humans and GenAI may shape cognitive engagement and cognitive outcomes over time. The framework draws upon a Neuro-Information-Systems (NeuroIS)-informed approach by integrating cognitive, behavioral, self-report, and neurophysiological perspectives into a multilevel account of how GenAI use shapes human cognition. We argue that cognitive engagement—the depth, persistence, and strategic quality of human processing during AI-supported tasks—is a proposed central mechanism linking the distribution and support of cognitive operations between humans and GenAI to cognitive outcomes. Direct effects on outcomes may coexist with engagement-mediated effects on outcomes. The cognitive consequences depend particularly on whether cognitively consequential operations related to understanding, learning, critical evaluation, and independent judgment continue to involve meaningful human engagement. Specifically, the framework integrates five elements: (1) antecedent conditions (user, task, and GenAI/system characteristics); (2) regulatory processes (metacognition, trust calibration, and motivational/goal regulation); (3) human–AI cognitive work configuration and cognitive engagement (i.e., how cognitive operations are distributed between the user and the AI system and how cognitively engaged the user remains); (4) short- and intermediate-term outcomes (performance, understanding, retention, and agency); and (5) long-term outcomes of cognitive sustainability and cognitive dependence. The article derives design principles for engagement-preserving AI and contributes to an interdisciplinary research agenda for examining these relationships through convergent behavioral, self-report, neurophysiological, and longitudinal evidence.