Generative AI in Advertising

The rapid evolution of Generative Artificial Intelligence (GenAI) tools, including technologies like Generative Adversarial Networks (GANs), Large Language Models (LLMs), and tools such as ChatGPT, Midjourney, and DALL·E, is transforming the landscape of digital marketing and advertising. This thesis examines the application of GenAI in the advertising industry, particularly focusing on how these tools reshape personalization, content creation, and consumer engagement. Through a systematic review of the literature, this study synthesizes fragmented analysis to provide a holistic understanding of how and why GenAI technologies are incorporated into advertising practices. It addresses the challenges marketers face, including ethical considerations regarding authenticity, data privacy, trust, and the strategic importance of human-AI collaboration in creative processes. By consolidating existing knowledge and determining gaps in the literature, the thesis offers actionable insights for marketing experts and industry stakeholders. The research underlines the potential of GenAI to improve scalability, efficiency, and hyper-personalization in advertising movements and campaigns while also stressing the need for standardized frameworks and ethical guidelines to ensure the reliability of AI use. The findings contribute to the growing body of research on AI in marketing, providing a foundation for future studies and practical applications of these transformative technologies.