Leveraging Artificial Intelligence to Enhance Market Intelligence for MSMEs in Bekasi, Indonesia: Challenges and Opportunities

Candra Dwi Hardiana (STIE Bisnis Internasional Indonesia (BII) Bekasi)
Abdisamad Abdirahman Omar (African Institute for Multidisciplinary Studies (AIMS), Somalia)
M. Yani Syafei (Universitas Ekuitas Indonesia (UEI) Bandung)
Muhammad Eko Purwanto (STIE Bisnis Internasional Indonesia (BII) Bekasi)

International Journal of Community Service (IJCS)
Vol. 5 No. 2 (2026): July-December

LEVERAGING ARTIFICIAL INTELLIGENCE TO ENHANCE MARKET INTELLIGENCE FOR MSMSs IN BEKASI, INDONESIA: CHALLENGES AND OPPORTUNITIES. This study examines the role of Artificial Intelligence (AI) in enhancing market intelligence among Micro, Small, and Medium Enterprises (MSMEs) in Bekasi Regency, West Java, Indonesia, within the context of digital transformation. Using a descriptive qualitative approach, data were collected through literature review, secondary data, and field observations from the Institution Collaboration for International Community Service 2026. The findings reveal a significant shift from intuition-based decision-making toward data-driven approaches, where AI enables MSMEs to analyze consumer behavior, predict market trends, and optimize digital marketing strategies. Furthermore, international collaboration within community service activities plays a crucial role in facilitating knowledge transfer and accelerating AI internalization, contributing to the development of digital awareness and strategic thinking among MSME actors. However, the study also identifies a substantial gap between AI potential and its actual implementation, driven by low digital literacy, limited technological access, and insufficient understanding of AI integration in daily business processes. These challenges highlight the need for a comprehensive ecosystem approach that includes policy support, continuous training, and infrastructure development. The study contributes to the literature by integrating theoretical perspectives with empirical findings, offering insights into the opportunities and challenges of AI adoption in MSMEs within developing regions.