Theoretical Approaches to Cybersecurity & Adversarial Attacks in AI-Driven Marketing: A Framework for Risk Mitigation

Abstract

The rapid development of artificial intelligence (AI) has transformed digital marketing, enabling businesses to achieve greater efficiency, improved returns on investment, and enhanced customer engagement. Despite these benefits, the widespread use of AI introduces significant challenges, including cybersecurity risks, adversarial attacks, and concerns about unethical handling of user data. These risks threaten data privacy and consumer trust, making it essential for organizations to implement effective risk mitigation strategies. By bridging the gap, this study proposed the risk mitigation strategies in AI-driven digital marketing frame work. Risk mitigation strategies include advanced technological measures, ethical AI practices, and organizational policies aimed at mitigating cyber threats while enhance customer confidence and security. Furthermore, on the principles of mediation theory, the research emphasizes the moderating role of sustainability in risk management and its contribution to ethical and long-term business practices in AI-driven marketing ecosystems.