Analysis of Factors Influencing the Adoption of Artificial Intelligence Assistants among Software Developers

Abstract

Software development in the era of global competition requires strategic technology management to enhance a company's competitiveness and economic performance. The main challenges in this process include project complexity, changing requirements, and time constraints, which often lead to project failures globally. In Indonesia, only 27% of information system projects are completed on budget and on time, highlighting significant issues in software development. AI assistants have emerged as an innovation with great potential to address these problems. With features such as code completion, code interpretation, and bug detection, this solution has the potential to increase software developers' productivity in the future. Given this context, this research aims to identify the factors influencing the intention to adopt AI assistants, particularly among software developers. The study was conducted using PLS-SEM and applied factors from common technology acceptance theories such as TAM and UTAUT. Data collection instruments were distributed using self-selection sampling and snowball sampling (N=165). Major factors in UTAUT such as effort expectancy, performance expectancy, facilitating conditions, and social influence were found to be significant in influencing attitudes or adoption intentions. Additionally, AI-specific factors in the context of UTAUT extension, such as AI literacy, were found to have an indirect effect on attitudes and behavioral intentions, moderated by other factors. It is hoped that the findings of this research can help stakeholders evaluate their strategies if they wish to adopt AI assistants and provide academic impact through scientific publications that can complement existing literature, expanding the understanding of AI integration in the professional IT realm.