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Purpose

This study examines how responsible and sustainable use intention (RSU) toward artificial intelligence-generated content (AIGC) image tools is formed in higher education art and design classrooms. Existing research has mainly explained generative AI use through technology acceptance or continuance logic, while paying limited attention to the aesthetic, authenticity-related and classroom-governance conditions under which long-term use becomes norm-compliant and educationally sustainable.

Design/methodology/approach

Drawing on the stimuli, organismic states and response (S–O–R) framework, this study models perceived usefulness, perceived ease of use and perceived classroom digital fairness as stimuli; digital aesthetic fatigue, authenticity–authorship anxiety and perceived authenticity of AIGC images as organismic states; and RSU as the response. GenAI literacy is included as a moderator. Data from 1,238 higher education art and design students were analysed using PLS-SEM, ANN and fsQCA.

Findings

Classroom use of AIGC image tools is better understood as a responsible post-adoption process than as a general technology acceptance issue. Perceived authenticity is the strongest positive predictor of RSU, digital aesthetic fatigue is the strongest negative factor, and authenticity–authorship anxiety also significantly inhibits RSU. GenAI literacy mainly functions as a boundary condition. High RSU is most likely to emerge from configurations characterised by high perceived authenticity and low digital aesthetic fatigue.

Originality/value

This study distinguishes RSU from general continuance intention and develops a unified framework integrating authenticity judgment, digital aesthetic fatigue, authenticity–authorship anxiety and perceived classroom digital fairness. It extends S–O–R by showing that long-term AIGC use in art education depends not only on technological perceptions, but also on authenticity confirmation, aesthetic sustainability and classroom governance.

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