Impact on Opportunities, Risks and Consumer Behavioral Intention of AI-Powered Personalization in Social Commerce

This study provides a statistical overview of digital payment usage and examines the relationships among artificial intelligence-based competencies and user behavioral intention in digital financial platforms. A total of 474 responses were collected in the middle of 2025 from Indonesian respondents using Purposive sampling, with 456 valid entries. Most respondents (96.2%) had used platforms such as PayPal, Wise, Payoneer, or Flip, predominantly young adults (87.1%) from Greater Jakarta. (Indonesia). The study employed a structural equation modeling (SEM) approach using SmartPLS to test the reliability, validity, and causal relationships among seven constructs: AI-TPACK, AI-TPK, Effort Expectancy, Perceived Ease of Use, Satisfaction, Social Influence, and Behavioral Intention. All indicators demonstrated acceptable reliability and validity. The model explained 70.2% of the variance in Behavioral Intention, indicating strong predictive power. Path coefficient analysis confirmed that AI-TPACK and AI-TPK significantly influence Effort Expectancy and Perceived Ease of Use, which in turn enhance Satisfaction and Social Influence. Both Satisfaction and Social Influence positively affect Behavioral Intention. The findings highlight the crucial role of AI-based knowledge and user experience factors in fostering acceptance and continued use of digital payment systems within social and digital commerce environments.