Generative AI and Cognitive Challenges in Research: Balancing Cognitive Load, Fatigue, and Human Resilience

This study examines the interaction between cognitive demands and generative artificial intelligence (GenAI) technologies in shaping the quality and influence of academic research. While GenAI tools such as ChatGPT and Elicit are increasingly adopted to ease information processing and automate repetitive tasks, their broader impact on researchers’ cognitive performance remains underexplored. Using data from 998 researchers and applying structural equation modeling (SEM-PLS), we examined the effects of cognitive load, task fatigue, and resilience on research outcomes, with GenAI immersion as a higher-order moderator. Results reveal that both cognitive load and fatigue negatively affect research quality, while engagement and resilience offer partial protection. Unexpectedly, high immersion in GenAI intensified the negative impact of cognitive strain, suggesting that over-reliance on AI can amplify mental burden rather than reduce it. These results enhance the design and responsible integration of AI technologies in academic environments by demonstrating that sustainable adoption necessitates a balance between efficiency and human creativity and resilience. The study provides evidence-based insights for researchers, institutions, and policymakers seeking to optimize AI-supported workflows without compromising research integrity or well-being.