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Justyna Dziedzic, University of Lodz, PolandAbstract
The increasing use of artificial intelligence (AI) in higher education is embedded in broader transformations of research evaluation systems, where productivity, citation metrics, and scholarly visibility play a central role. This presentation examines how AI tools influence knowledge production under conditions of metric-driven evaluation and explores their implications for the sustainability of academic work. Adopting a conceptual and analytical perspective grounded in humanistic management and knowledge production theory, the study approaches AI as a factor that reinforces metric-oriented logic in academia. AI-supported tools accelerate content generation, optimize outputs for visibility, and enhance strategic management of research activities. Within this context, three key tensions are identified: (1) increased efficiency of knowledge production versus intensified productivity pressure, (2) metric optimization versus the risk of standardization and reduced epistemic depth, and (3) broader access to AI tools versus emerging inequalities in digital competencies and resource availability. The analysis suggests that AI not only supports knowledge production but also amplifies existing evaluation mechanisms, producing ambivalent effects on the sustainability of academic work. The presentation argues that AI should be understood as a driver of intensified metric control, calling for a critical reassessment of knowledge management practices in contemporary higher education.
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