AI-Driven Transformation of Digital Advertising Strategies Through Machine Learning and Predictive Personalization

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing digital advertising by enabling intelligent automation, real-time personalization, and predictive consumer analysis. This study explores the influence of AI-powered advertising strategies on the purchase intention of Indian online consumers aged between 18 and 30 years. The research combines technological dimensions such as personalization and predictive analytics with psychological factors including consumer trust, perceived advertisement relevance, and privacy concerns to develop an integrated analytical framework. A descriptive and analytical research methodology was adopted, and primary data were collected from 150 respondents through a structured questionnaire using a five-point Likert scale and convenience sampling technique. Reliability testing was conducted using Cronbach’s Alpha, while correlation and multiple regression analyses were applied to evaluate the proposed hypotheses. The findings indicate that AI-based personalization and predictive targeting significantly improve advertising effectiveness, customer engagement, and purchase intention. Consumer trust and ad relevance positively influence acceptance of AI-driven advertisements, whereas privacy concerns negatively affect user perception and adoption. The study concludes that ethical AI implementation, transparent data practices, and trust-oriented advertising approaches are essential for maximizing the effectiveness of modern digital marketing strategies.