Engineering Intelligence In Social Commerce: Ai-Driven Product Architectures For The Creator Economy

Abstract

The present study explores the transformative impact of AI-driven product architectures on the evolving dynamics of the creator economy within social commerce platforms. By employing a mixed-methods approach that integrates quantitative modelling and qualitative analysis, the research examines how artificial intelligence enhances creator performance, consumer engagement, and operational efficiency. Quantitative findings reveal that algorithmic personalisation (β = 0.411) and AI adoption level (β = 0.342) are the most significant predictors of creator success, collectively explaining 77% of performance variance. Correlation analysis further demonstrates strong associations between personalisation, engagement, and conversion rates, underscoring the centrality of adaptive intelligence in driving digital interaction outcomes. Thematic insights highlight critical ethical dimensions such as algorithmic transparency, creator autonomy, and data fairness, emphasising the necessity for responsible AI governance. The radar and cluster analyses illustrate how social commerce platforms like Instagram, YouTube, TikTok, and Pinterest are converging toward standardised AI architectures that balance automation with creativity. Overall, the study concludes that engineering intelligence, the systematic integration of AI in digital architecture design, serves as a catalyst for innovation, sustainability, and inclusivity in the creator economy.