Businesses face intense competition and fluctuating consumer preferences, driven by social media, global events, and technological innovations. This study systematically reviews the literature (2019–2024) to analyze the role of big data and artificial intelligence (AI) in identifying market trends, exploring their potential, challenges, and implementation strategies. Using the systematic literature review method, peer-reviewed articles were obtained from Scopus, ScienceDirect, IEEE Xplore, and Google Scholar. Keywords used include big data, AI, market trends, and consumer behavior. A qualitative-descriptive analysis was employed to synthesize findings related to technology applications, effectiveness, and barriers. The results confirm that AI algorithms (such as machine/deep learning) significantly improve the accuracy of trend detection by processing real-time data from social media, search engines, and e-commerce. Big data enables more detailed consumer segmentation and personalized marketing, while AI-based tools enhance demand forecasting and campaign responsiveness. MSMEs are increasingly adopting affordable AI platforms for data-driven decision making. Key challenges include data privacy risks, infrastructure gaps, and workforce skill shortages. The integration of big data and AI has proven transformative for market analysis, but requires ethical regulation, digital literacy initiatives, and inclusive infrastructure to ensure sustainable impact.
Copyrights © 2025