The study investigate how AI-based applications are used to influence strategic decision-making in digital marketing and consumer intent with consideration to three goals connected with AI-driven personalization, predictive analytics, and AI-driven insights. A quantitative research design was applied to collect data on 200 digital marketing professionals in Delhi NCR using a structured questionnaire and then analyzed using “descriptive statistics, correlation and regression analysis”. The results indicate that AI-based personalization is weak but significant in regard to consumer intent, whereas predictive analytics is stronger, as it explains 13.6% difference in consumer intent and purchase behavior. Additionally, AI-based insights appeared to have a weak positive association with digital marketing performance, which could indicate that AI-based data interpretation leads to improved campaigns and more strategic alignment. The outcomes all point towards the fact that state-of-the-art AI tools and especially predictive analytics and insights generation have a positive effect on the enhancement of marketing performance. The study finds that organizations should develop analytical and AI capacities to stay competitive, yet the use of self-reported data, regional sample, and cross-sectional design do not allow causal inferences.