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Pal, Shreyashi (2024) Artificial Intelligence Technology Acceptance: A survey based perception study using UTAUT. Masters thesis, Dublin, National College of Ireland.
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Abstract
Artificial intelligence (AI) technology is garnering a lot of attention from academics as well as businesses. The use of AI is increasing within business management, whilst it continues to be an important topic of discussion within the tech world. While a lot has been researched around the advantages and disadvantages of using AI, and the challenges that AI technology adoption brings, current literature is scarce when it comes to people’s attitude around AI technology, is it being accepted by professionals or not? Technology adoption models and theories have been researched for decades now, since for any technology to be successful, it must be accepted and used by people. This study aims at evaluating the overall attitude, of professionals working within Ireland, while further finding the factors that impact this perception, and presents a model grounded in the UTAUT (Unified theory of acceptance and use of technology). The descriptive research uses a quantitative method of research, gathering primary data through an online survey, replicating a questionnaire from a global study with similar research intent. The results show overall positive attitude towards AI technology acceptance, in line with the global study, while a strong correlation was identified between UTAUT constructs Performance expectancy, Effort expectancy, Social Influence, Facilitating Conditions, and proved that “trust” is a significant factor that impacts the behavioural intention and actual use behaviour, while the data analysis showed the moderators, Age and Gender, did not have a significant impact on the attitude, but income level impacted the construct “Trust”, among the Irish professionals, participants in the survey. A simplified model was proposed based on the hypotheses testing, correlation testing, factor analysis, linear regressions, and cross-tabulation, where these factors, constructs, and moderators were brought together.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Armendáriz, Fabián UNSPECIFIED |
| Subjects: | Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence H Social Sciences > Economics > Business |
| Divisions: | School of Business > Master of Science in Management |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 12 Aug 2025 12:44 |
| Last Modified: | 12 Aug 2025 12:44 |
| URI: | https://norma.ncirl.ie/id/eprint/8518 |
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