Harnessing AI-Driven Consumer Insights for Strategic Innovation and Business Decision-Making: A Systematic Literature Review

Abstract

The rapid advancement of Artificial Intelligence (AI) has transformed how organizations generate and utilize consumer insights to support strategic innovation and business decision-making. Despite the growing body of research on AI applications in marketing, analytics, and innovation, the literature remains fragmented, limiting a comprehensive understanding of the strategic role of AI-driven consumer insights. Therefore, this study aims to systematically review the existing literature and examine how AI-driven consumer insights contribute to strategic innovation and organizational decision-making. This study employed a Systematic Literature Review (SLR) approach following the PRISMA 2020 guidelines. Relevant studies were identified from ScienceDirect and Google Scholar using predefined search keywords. After applying the inclusion and exclusion criteria, 21 peer-reviewed articles published between 2021 and 2025 were selected for analysis. The findings indicate a growing research interest in AI-driven consumer insights, with Machine Learning, Predictive Analytics, Big Data Analytics, and Natural Language Processing emerging as the most widely adopted technologies. These technologies enable organizations to better understand consumer behavior, identify market opportunities, anticipate emerging needs, and support innovation and evidence-based decision-making. Furthermore, the review highlights several future research directions, including Explainable AI, AI ethics and governance, human–AI collaboration, and real-time consumer analytics. This study contributes to the literature by providing an integrated understanding of the relationship between AI-driven consumer insights, strategic innovation, and business decision-making, while offering practical implications for organizations seeking to leverage AI as a strategic resource.