Czynniki wpływające na akceptację sztucznej inteligencji przez księgowych: rozszerzony model akceptacji technologii uwzględniający lęk technologiczny i doświadczenie
Factors that influence accountants’ acceptance of Artificial Intelligence: An extended Technology Acceptance Model that incorporates technology anxiety and experience

Summary/Abstract: Purpose: This study investigates the factors that influence accountants’ readiness to adopt artificial intelligence (AI) technologies in their professional practice, with a particular focus on the roles of technology anxiety, AI experience, and professional experience within an extended Technology Acceptance Model (TAM) framework. Methodology/approach: A survey was conducted among 72 chief accountants and accounting professionals in Polish industrial enterprises. The research employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to test hypotheses regarding the relationships between perceived usefulness, perceived ease of use, attitude toward AI, anxiety, experience factors, and behavioral intention to adopt AI. Findings: The results confirm that perceived usefulness and ease of use significantly influence attitudes toward AI adoption. Technology anxiety emerges as a significant barrier, negatively affecting attitudes toward AI use. Prior AI experience positively influences both perceived ease of use and usefulness, while firm-specific experience shows no significant effect on perceived usefulness. Research limitations/implications: The study’s sample size and cross-sectional na-ture limit generalizability. Future research should employ longitudinal designs with larger, more diverse samples to validate these relationships across different contexts and track how perceptions evolve over time. Originality/value: This research contributes to the literature by integrating anxiety and experience factors into the TAM framework, specifically for AI adoption in accounting. The findings provide practical insights for organizations seeking to facilitate AI implementation by addressing psychological barriers and leveraging experience-based factors.

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