Paradoks sztucznej inteligencji: jak poleganie na sztucznej inteligencji może prowadzić do erozji wiedzy eksperckiej w rachunkowości
The AI paradox: How AI dependence may erode accounting expertise

Summary/Abstract: Purpose: The paper explores the long-term consequences of artificial intelligence (AI) integration in accounting, focusing on two interrelated challenges: AI models’ lack of transparency and the disruption of expertise development resulting from the automation of foundational tasks. Methodology/approach: The study employs a discursive qualitative approach based on a narrative literature review and conceptual synthesis. It draws on theoretical frame-works of skill acquisition, cognitive apprenticeship, and tacit knowledge to analyse how AI technologies are reshaping professional learning pathways and the development of judgement. Findings: AI models’ opacity undermines interpretability and accountability, creating ethical and regulatory challenges that may hinder compliance with accounting principles. The automation of fundamental accounting tasks limits experiential learning opportunities for early-career professionals, thereby impeding their capacity to exercise critical judgement. When reflectively implemented, AI may also serve as a cognitive scaffold that enhances analytical reasoning and knowledge transfer. However, without such reflection, automation and opacity can interact to form a self-reinforcing cycle that gradually erodes professional expertise. Practical implications: The paper highlights the need for deliberate AI governance, professional education reform, and mentoring systems that balance automation efficiency with human interpretive capacity.Originality/value: By linking algorithmic opacity and skill degradation within a unified theoretical framework, the study conceptualises the AI paradox – the coexistence of efficiency gains and expertise erosion – and offers a foundation for future empirical research.

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