AI-Powered Creative Optimization in Ad Serving
Year: 2025
Type: article
Abstract: AI-powered creative optimization has fundamentally transformed digital advertising by enabling sophisticated data analysis, dynamic personalization, and automated testing methodologies previously unattainable through manual processes. This technical review explores how artificial intelligence and machine learning algorithms have revolutionized ad serving, shifting the industry from static, uniform approaches to highly personalized experiences tailored to individual user preferences. The integration of these advanced technologies has significantly compressed optimization cycles, reduced customer acquisition costs, and improved conversion rates across diverse industry sectors. Through a comprehensive article of data collection frameworks, automated creative testing methodologies, real-time adaptation technologies, and personalization algorithms, this review provides insights into the technical infrastructure powering these capabilities. Additionally, it addresses emerging technologies shaping the future landscape, including generative AI, neuromorphic computing, quantum computing applications, and explainable AI frameworks, while acknowledging persistent challenges related to latency, cold-start problems, privacy regulations, and model drift. The review concludes by exploring integration opportunities with broader marketing technology ecosystems to achieve unified optimization across multiple channels
Author: Subhash Vinnakota
Institution: Walt Disney (United States)
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6911794129
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