Paper Type

ERF

Abstract

Generative artificial intelligence (GenAI) is transforming how individuals learn, work, and create, yet traditional technology acceptance models may not fully explain its adoption. This study proposes an extended GenAI Acceptance Model by integrating TAM and UTAUT with GenAI-specific constructs, including perceived creativity, reliability concerns, ethical-legal risks, and trust. Unlike traditional information systems, GenAI functions as a semi-autonomous cognitive collaborator that offers creative augmentation while raising concerns about hallucinations, bias, privacy, and copyright. Using a quantitative survey and Structural Equation Modeling (SEM), the study will examine how traditional acceptance factors and GenAI-specific perceptions influence behavioral intention and actual use. The proposed model is expected to contribute to Information Systems research by offering a more comprehensive framework for understanding GenAI adoption and providing practical guidance for responsible implementation.

Paper Number

1274

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Aug 15th, 12:00 AM

Toward a New Model of GenAI Acceptance: Extending TAM and UTAUT

Generative artificial intelligence (GenAI) is transforming how individuals learn, work, and create, yet traditional technology acceptance models may not fully explain its adoption. This study proposes an extended GenAI Acceptance Model by integrating TAM and UTAUT with GenAI-specific constructs, including perceived creativity, reliability concerns, ethical-legal risks, and trust. Unlike traditional information systems, GenAI functions as a semi-autonomous cognitive collaborator that offers creative augmentation while raising concerns about hallucinations, bias, privacy, and copyright. Using a quantitative survey and Structural Equation Modeling (SEM), the study will examine how traditional acceptance factors and GenAI-specific perceptions influence behavioral intention and actual use. The proposed model is expected to contribute to Information Systems research by offering a more comprehensive framework for understanding GenAI adoption and providing practical guidance for responsible implementation.