Revolutionizing Imaging Design Content With AIGC: User-Centered Challenges, Opportunities, and Workflow Evolution
Zijian Zhu, Tao Yu, Yijing Wang, Junping Xu · IEEE Access · 2025
This study examines the influence of Artificial Intelligence Generated Content (AIGC) technology on the workflows and career trajectories of designers. Using the Technology-Organization-Environment (TOE) framework, a mixed-methods approach was employed, integrating expert interviews and quantitative surveys. Semi-structured interviews identified ten primary influencing factors, which were further analyzed through a survey of 531 users to quantify the interrelationships among these factors. Results indicate that career paths and industry environment exert the most significant positive impact on designers’ behavioral intentions, highlighting the rising demand for AIGC and its potential to enhance career prospects. Output availability and cross-functional collaboration demonstrate practical benefits in improving content quality and team efficiency. Technological maturity and public acceptance serve as key adoption drivers, while social construction and innovation underscore AI’s capacity to foster creativity and design diversity. Ethics and privacy reflect user concerns over data security, whereas learning costs negatively affect adoption due to perceived complexity. This study confirms the utility of the TOE framework in guiding the deployment of AIGC technology and underscores the necessity of promoting AI’s sustainable development in design. It provides theoretical, practical, and policy recommendations, including improving the usability and innovation of AIGC tools, strengthening support for team collaboration, and offering career development training for designers. Furthermore, policymakers are urged to address privacy and ethical challenges to ensure the long-term sustainable adoption of AI. This research delivers critical theoretical and practical insights into integration of AIGC in the design field.