Adoption of Generative Artificial Intelligence: The Roles of Perceived Usefulness, Self-Efficacy, and Workload

As generative artificial intelligence (Generative AI) continues to advance rapidly, its applications have become increasingly prevalent. However, uncertainties persist regarding users' attitudes and willingness to adopt Generative AI. This study integrates Task-Technology Fit and Self-Efficacy Theories to examine key factors influencing Generative AI adoption. The study conducted an empirical survey (n=336) and revealed that workload, AI self-efficacy, and perceived usefulness significantly impact adoption. These findings contribute to theoretical advancements and offer practical recommendations for facilitating Generative AI implementation in business contexts.