<![CDATA[This study investigates the ethical considerations in the deployment of artificial intelligence (AI) for customer profiling by employing a qualitative literature-based research methodology. With AI-driven profiling systems becoming central to consumer analytics, companies now have unprecedented capabilities to personalize interactions, segment audiences, and predict behavior. However, this technological progress is accompanied by pressing ethical concerns related to privacy, informed consent, algorithmic bias, transparency, and psychological manipulation. The research synthesizes insights from 45 scholarly articles, regulatory documents, and industry reports, applying qualitative document analysis to identify thematic patterns in ethical challenges and organizational responses. The findings reveal two major thematic domains: first, the emergence of ethical tensions in AI systems, including concerns over data commodification, opacity of algorithms, and discriminatory profiling practices; second, the varied and often fragmented organizational approaches to ethical governance, ranging from aspirational guidelines to practical gaps in implementation. While there is growing awareness of responsible AI principles—such as fairness, accountability, transparency, and explainability—many organizations continue to struggle with embedding these values into their AI lifecycle. This study contributes to the literature by offering a conceptual framework that bridges theoretical ethics and applied governance, and emphasizes the importance of sustained organizational commitment, participatory design, and ethical foresight. Ultimately, the research highlights the need for a paradigm shift in both academia and industry, where ethics in AI moves from peripheral compliance to core strategic practice.]]>
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