Paper Type

Short

Paper Number

PACIS2026-1650

Description

The integration of artificial intelligence (AI) into work and everyday life occurs not by chance but for some reasons. Studies report diverse behavioural responses to generative AI (GenAI) in higher education, from enthusiastic to defensive. However, the conditions that enable or constrain this integration remain insufficiently understood. This paper develops a socio-technical model, WSTT (will, skill, technology, and task), to explain how the integration of GenAI in higher education (an illustrative example of knowledge work) emerges from individual-technology-institutional interplay of mechanisms. Actor-tool interactions occur within institutional structures that encompass shared norms, discipline, and knowledge systems to shape action. When such mechanisms are activated, they may generate five patterns/events of GenAI integration, including non-use, substitution, augmentation, modification, and redefinition. The model offers a theoretically grounded framework for identifying enablers and barriers to GenAI integration and guides supportive changes in training, work design, or policies that may facilitate effective integration.

Comments

04-DigitalLearning

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Jul 5th, 12:00 AM

Will, Skill, Tool or Task? Investigating the Mechanisms for Generative AI Integration in Higher Education

The integration of artificial intelligence (AI) into work and everyday life occurs not by chance but for some reasons. Studies report diverse behavioural responses to generative AI (GenAI) in higher education, from enthusiastic to defensive. However, the conditions that enable or constrain this integration remain insufficiently understood. This paper develops a socio-technical model, WSTT (will, skill, technology, and task), to explain how the integration of GenAI in higher education (an illustrative example of knowledge work) emerges from individual-technology-institutional interplay of mechanisms. Actor-tool interactions occur within institutional structures that encompass shared norms, discipline, and knowledge systems to shape action. When such mechanisms are activated, they may generate five patterns/events of GenAI integration, including non-use, substitution, augmentation, modification, and redefinition. The model offers a theoretically grounded framework for identifying enablers and barriers to GenAI integration and guides supportive changes in training, work design, or policies that may facilitate effective integration.