Acceptance of Generative AI in the Creative Industry: Examining the role of Brand Recognition and Trust in the AI adoption

This study explores the factors influencing the adoption of Generative AI text-to-image tools in the creative industry, using an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model. The objective is to assess how brand recognition and trust, alongside performance expectancy, effort expectancy, facilitating conditions, and social influence, shape the behavioral intention to use Generative AI tools. While previous research has emphasized the importance of UTAUT constructs in technology adoption, the influence of brand equity factors remains underexplored. This study bridges this gap and provides insights to enhance adoption strategies. Standardized questionnaires were used, incorporating UTAUT constructs and brand-related variables such as Brand Recognition and Brand Trust. The sample consisted of individuals working in the creative industry in the US and Spain, with 208 valid responses. The survey was distributed through creative online communities. Partial Least Squares Structural Equation Modeling was employed to validate the hypotheses, ensuring reliable and valid results. Key findings indicate that performance expectancy, facilitating conditions, and brand trust positively influence the behavioral intention to use Generative AI tools, while brand recognition negatively influences behavioral intention. Social influence and effort expectancy did not present statistically significant results. These insights contribute to developing effective adoption strategies for Generative AI in the creative industry.