Integrating Task–Technology Fit and AI Transparency to Explain Artificial Intelligence Adoption: The Mediating Role of AI Trust

Abstract

The present study aims to explore how AI can be adopted in governmental ministries in Oman by combining the Task–Technology Fit theory with AI Transparency and AI Trust. A structured questionnaire was used in collecting data from 392 employees from Ministry of Justice, Ministry of Transport, Communications and Information Technology and Ministry of Health. Using SmartPLS, the measurement and structural models were assessed by means of Partial Least Squares Structural Equation Modelling (PLS-SEM). The results reveal that Task Characteristics and Technology Characteristics significantly impact Task–Technology Fit, which in turn positively affects AI Trust and AI Adoption, and AI Transparency positively influences AI Trust and AI Adoption. AI Trust also plays an important role in AI Adoption and serves as a mediator between Task–Technology Fit and AI Transparency and AI Adoption. Task–Technology Fit was accounted for by the model to the extent of 51.7%, AI Trust to the extent of 40.1% and AI Adoption to the extent of 41.8%. These findings highlight the importance of functional alignment, transparently managed systems, and employee trust, providing practical insights for implementing and governing AI in the public sector. The results support all seven direct and two mediation hypotheses proposed.