This study investigates the integration of Artificial Intelligence (AI), Digital Marketing Information Systems (DMIS), and Marketing Management to enhance decision-making processes in marketing. The research aims to explore the extent of augmentation in marketing decision-making, identify indications of objectiveness in AI-driven analytics, and propose solutions to ensure transparency and accountability. Methodologically, the study conducts a systematic literature review to synthesize existing research on the topic. Findings suggest that AI technologies offer advanced analytics capabilities, enabling marketers to gain deeper insights into consumer behavior and market trends. However, concerns regarding biases in AI-driven analytics and challenges in data integration and dissemination are identified. The study underscores the importance of interdisciplinary collaboration, transparency, and explainability in AI algorithms to mitigate biases and enhance objectiveness. Moreover, it highlights the need for robust data governance policies and talent development initiatives to foster a culture of data-driven decision-making. The research contributes to theoretical understanding by redefining marketing practices through AI integration and offers practical insights for organizations to leverage AI, DMIS, and Marketing Management effectively.
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