Analysis on ChatGPT user acceptance as a daily assistance AI tool in Melaka

This study examines the factors influencing user acceptance of ChatGPT as a daily reference tool in Melaka, Malaysia and assesses varying levels of user adoption. Utilizing an integrated model based on the Technology Acceptance Model (TAM) and incorporating external constructs such as Privacy and Security, the research provides an in-depth understanding of user acceptance by measuring diverse perspectives. A quantitative research approach was employed, surveying 357 ChatGPT users in Melaka to evaluate attitudes, beliefs, and behaviors related to adoption. The results highlight that perceived ease of use (β = 0.300, p < 0.001), perceived usefulness (β = 0.200, p < 0.001), and security (β = 0.270, p < 0.001) significantly predict behavioral intention, while privacy concerns were found to be statistically insignificant (β = 0.006, p = 0.876). The study also reveals strong correlations between ease of use and behavioral intention (r = 0.959), underscoring the importance of user friendly design in AI adoption. These findings align with the TAM framework and extend its applicability to AI tools, offering practical insights for developers, policymakers, and educational institutions. The research contributes to bridging the gap between technology and users by shedding light on actual user experiences and considerations, thereby informing the design of more intuitive, secure, and user-centric AI systems. Additionally, the study addresses cultural and contextual factors specific to Melaka, suggesting that users prioritize utility and security over privacy. Recommendations are provided to enhance ChatGPT’s adoption, including improving interface design, strengthening security measures, and integrating AI literacy programs in educational settings. The study’s limitations, such as potential biases in self-reported data and a geographically limited sample, are acknowledged, with suggestions for future research to explore cross-cultural variations and longitudinal adoption trends.