Predicting Adoption Intention of Artificial Intelligence A Study on ChatGPT

Main Article Content

Md Mehedi Hasan Emon
Farheen Hassan
Mehzabul Hoque Nahid
Vichayanan Rattanawiboonsom

Abstract

This study focuses on predicting the adoption intention of ChatGPT among Professionals in Bangladesh. ChatGPT, powered by natural language processing and artificial intelligence, has the potential to revolutionize communication and enhance productivity in professional settings. The Unified Theory of Acceptance and Use of Technology (UTAUT) is used as a theoretical framework to examine the variables that affect the adoption intention of ChatGPT. The study aims to understand the impact of attitude towards AI, performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, trust, behavioral intention to use, and actual use of ChatGPT among Professionals in Bangladesh. The research questions explore the relationships between these variables. The objectives of the study are to examine the relationship between attitude towards AI and behavioral intention to use ChatGPT, investigate the impact of performance expectancy and effort expectancy on behavioral intention to use, explore the effect of social influence and facilitating conditions on behavioral intention to use, assess the relationship between hedonic motivation and behavioral intention to use, investigate the influence of trust on behavioral intention to use, and analyze the relationship between behavioral intention to use and actual use of ChatGPT. The findings provide valuable insights into the factors influencing the adoption intention and actual use of ChatGPT. The study highlights the significance of strengthening behavioral intentions, emphasizing performance benefits and building trust, and creating facilitating conditions to promote adoption and utilization. The research contributes to the understanding of factors influencing the adoption and usage behavior of ChatGPT and offers practical implications for organizations and policymakers to maximize the benefits of artificial intelligence applications in the context of Bangladeshi Professionals.

Article Details

How to Cite
[1]
M. M. Hasan Emon, F. Hassan, M. Hoque Nahid, and V. Rattanawiboonsom, “Predicting Adoption Intention of Artificial Intelligence”, AJSE, vol. 22, no. 2, pp. 189 - 199, Aug. 2023.
Section
Articles

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.