Electronic Commerce Systems Development: Exploring the Best Practice for Artificial Intelligence Applications

Purpose: This study explores best practices for developing artificial intelligence appli-cations in electronic commerce businesses and examines factors that may influence the adoption of such applications in this sector.Study design/methodology/approach: A quantitative research approach was employed, using a survey questionnaire for data collection and structural equation modeling for data analysis. Sample and data: A total of 264 valid responses were obtained from participants who are currently employed, utilize technology in their professional activities, hold current or pre-vious managerial roles, work in businesses that sell products or provide services online, and incorporate artificial intelligence into their work practices.Results: The findings indicate that businesses prefer in-house development of artificial intelligence applications to maintain competitive advantage by leveraging real business data for artificial intelligence training. Moreover, the characteristics of artificial intelligence technology and organizational capabilities significantly and positively affect the adoption of new artificial intelligence applications in electronic commerce businesses. Originality/value: The study addresses critical gaps by identifying best practices for developing artificial intelligence applications in electronic commerce businesses, emphasizing the importance of data management, privacy, and governance, as well as offering a framework for the adoption of artificial intelligence applications.Research limitations/implications: The study is limited by a small sample size and focuses solely on electronic commerce businesses. The results of this research can guide electronic commerce businesses in making informed decisions about adopting new artificial intelligence solutions aligned with their operational goals.