Intention to Use Artificial Intelligence Among SME Account Executives

Gehad Mohammed Ahmed Naji^1*Muhammad Shoaib Saleem²Lim Cheah³Khairul shafee kalid⁴Yulita Hanum P Iskandar^3*

• ¹Universiti Sains Malaysia, Penang, Malaysia
• ²INTI International University, Nilai, Malaysia
• ³Universiti Sains Malaysia, Minden Heights, Malaysia
• ⁴Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia

Purposes: The study investigated the intention of account executives from Small and Medium Enterprises (SMEs) to employ artificial intelligence at their workplace. This study will examine the Unified Theory of Acceptance and Use of Technology (UTAUT), as well as technological and personal characteristics, and the role of SME account executives in adopting artificial intelligence. This study addresses the knowledge gaps in SME account executives' understanding of artificial intelligence. Methodology: employed an online questionnaire distributed in collaboration with SMEs in Malaysia to gather responses from 273 account executives who work in SMEs. The data were analysed using PLS-SEM and Artificial Neural Networks (ANN) to investigate SME account executives' intentions to employ artificial intelligence. The demographic information of the individuals was analysed using SPSS software. Results: The study's findings revealed positive and significant relationships between performance expectancy, effort expectancy, social influence, facilitating conditions, system quality, employee awareness, and personal innovativeness toward artificial intelligence. Insignificant relationships were found between time-saving features and technological self-efficacy, and a negative, significant relationship existed with internet technology (IT) features toward artificial intelligence. Limitation: The cross-sectional approach focuses on SMEs in Malaysia, where the study's applicability to other industries and countries is limited due to changes in the cultural, economic, and regulatory environment. Because participants may give socially acceptable answers rather than honest ones, using self-reported data raises the possibility of bias. Because inquiry assumes a certain level of knowledge with AI technology, respondents' varying levels of digital competency may influence the findings. Practical Implication: The findings of this study can help SMEs adopt artificial intelligence for their operations, particularly in accounting departments. Collaboration among organisations can help improve employee motivation to increase intention to use artificial intelligence. Originality/Value: This study uses the Unified Theory of Acceptance and Use of Technology (UTAUT), technical qualities, and individual traits.