From Algorithms to Authenticity: Ensuring Ethical Customer Engagement in the Age of Artificial Intelligence

Mohammed Nadeem

International Journal of Business and Management, 2025, vol. 20, issue 2, 13

Abstract: Integrating artificial intelligence (AI) into customer engagement practices transforms how organizations interact with consumers and offers enhanced personalization and efficiency. However, this technological evolution introduces significant ethical challenges, including algorithmic bias, data privacy violations, and a potential decline in consumer trust. This research, Algorithms to Authenticity (ATA), investigates the intricate relationship between AI technologies and authentic, ethical engagement strategies. The central idea of the research study is to explore three main questions- 1. How can businesses effectively implement AI technologies to improve customer engagement ethically? 2. What are the ethical dilemmas and potential risks associated with AI-driven customer engagement? 3. How can transparency and authenticity be maintained in AI-driven interactions to foster trust? The study emphasizes the urgent need for businesses to transition from an algorithm-centric model to one that prioritizes authenticity. This research analyzed ethical concerns for maintaining consumer trust and loyalty. The result of the study aims to provide actionable insights to help businesses navigate the ethical challenges posed by AI to reinforce the commitment to ethical standards while enhancing consumer satisfaction. The study's findings advocate for transparency, accountability, and proactive measures mitigating the risks associated with AI deployment. Given the findings, the three key directions of the study are promoting ethical AI implementation, addressing risks associated with algorithmic misuse, and enhancing transparency to foster authentic customer relationships and trust, reinforced by the concept of ATA ensuring ethical customer engagement. The directions guide organizations, researchers, and policymakers toward ethical AI practices.

Date: 2025
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