AI in Strategic Marketing: Leveraging Machine Learning for Consumer Behavior Prediction - A Case Study of MSMEs in Selangor - Salamiah Kulal Salamiah; Dorris Yadewani; Dona Ikranova Febrina; Mukti Diapepin; Yerizal Yerizal (International Journal of Islamic Business and Management Review, 2026)
Purpose – This study aims to investigate the transformative impact of artificial intelligence (AI) and machine learning (ML) on strategic marketing, specifically focusing on consumer behavior prediction among Micro, Small, and Medium Enterprises (MSMEs) in Selangor, Malaysia. Methodology – A quantitative approach was employed, collecting cross-sectional data from 150 [sesuaikan angka sampel Anda] MSME owners and managers. The data were analyzed using Structural Equation Modeling (SEM-PLS) to evaluate how AI-driven predictive models influence marketing effectiveness and targeting accuracy. Findings – The results reveal that AI-based models significantly enhance marketing precision. MSMEs that integrated these technologies reported a 34% increase in customer engagement and a 28% improvement in conversion rates compared to traditional methods. Furthermore, the study highlights that digital readiness and ethical data usage are key drivers for AI adoption in the local business landscape. Originality – This research contributes to the literature by bridging the gap between advanced technology adoption and MSME marketing strategies within an emerging Islamic market hub. The findings provide practical insights for MSME digital transformation and offer policy recommendations for stakeholders in Selangor to foster a more data-driven and ethically aligned business environment.