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Evaluating designers' acceptance of AI generated content using TAM and TRI frameworks
Shao-Feng Wang1, Ke-Yi Liu2, Yang Liu2
1FuZhou University, No.852, LiGong. Rd., Ji'mei Dist., Xiamen City, FuJian Province, China. t09302@fzu.edu.cn.
Scientific Reports
|May 5, 2026
Summary
Designers are more likely to adopt AI-generated content (AIGC) when it is perceived as easy to use and they possess high technology readiness. Personal traits like innovativeness and optimism significantly influence this adoption, highlighting areas for improvement in AI integration for creative fields.
Area of Science:
- Human-Computer Interaction
- Artificial Intelligence in Creative Industries
- Technology Adoption
Background:
- Artificial intelligence (AI) can automate repetitive tasks, but its role in innovative fields like art and design is debated.
- Understanding designers' acceptance of AI-generated content (AIGC) is crucial for its integration into the creative industry.
Purpose of the Study:
- To explore designers' acceptance of AIGC using the Technology Acceptance Model (TAM) and Technology Readiness Index (TRI).
- To analyze factors influencing designers' intention to use AIGC and identify key antecedents.
Main Methods:
- Utilized the Technology Acceptance Model (TAM) and Technology Readiness Index (TRI) frameworks.
- Investigated the relationship between perceived ease of use, perceived usefulness, technology readiness, personal traits, and AIGC usage intention among designers.
Main Results:
- Perceived ease of use and technology readiness were primary drivers for AIGC adoption.
- Perceived usefulness did not significantly impact usage intention, suggesting AI knowledge dissemination is advanced.
- Designer traits (innovativeness, optimism, insecurity) influenced intention via perceived ease of use, with insecurity noted as an improvement area.
Conclusions:
- The TAM requires adaptation for the creative design field, integrating subjective elements like TRI.
- Technology readiness and personal traits are critical for AIGC acceptance in design.
- Findings provide theoretical and empirical support for integrating AI into the art and design industry.
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