AI Recommendation Systems and Digital Promotion Effectiveness on TikTok Social Commerce in Indonesia - Efi Ero Sofia; Eko Aziz Apriadi; Ribut Julianto; Muawan Bisri (Universitas Darul Ulum, 2026)
The development of artificial intelligence has brought fundamental changes to the social commerce ecosystem, particularly on the TikTok platform, which has now become one of the largest online shopping channels in Indonesia. This study aims to analyze the effect of the artificial intelligence recommendation system on the effectiveness of digital promotion on the TikTok platform in Indonesia, while considering the moderating roles of user trust and privacy concerns. The method used is quantitative, with a cross-sectional survey design involving 320 active TikTok users aged 17–45 years. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) through SmartPLS 4.0 software. The results show that the AI recommendation system has a positive and significant effect on both user engagement (β = 0.612) and purchase conversion (β = 0.548). User trust was found to strengthen this relationship, while privacy concerns significantly weakened it. These findings confirm that the effectiveness of AI-based promotion does not depend solely on the sophistication of the algorithm, but also on the ecosystem of trust built among the platform, marketers, and consumers. This study provides practical contributions for digital business actors in Indonesia in designing promotional strategies that are more human-centered and responsible.