Impact of AI-Driven Marketing Strategies on Consumer Purchase Intention in Northern India’s Fashion Industry

This study examines the impact of Artificial Intelligence (AI) on marketing communication strategies in the fashion industry of Northern India. With the increasing adoption of AI in marketing, fashion brands are leveraging predictive analytics, chatbots, and virtual assistants to enhance personalization, customer engagement, and brand loyalty. The study focuses on five metropolitan cities—Delhi, Chandigarh, Jaipur, Lucknow, and Kanpur—where data was collected from 100 marketing professionals and 500 frequent fashion consumers. A mixed-method approach was employed, integrating surveys and interviews, while statistical tools such as regression analysis and exploratory factor analysis were used to analyze AI’s influence. The findings reveal that AI-driven personalization significantly improves consumer interactions and purchasing decisions. Predictive analytics helps brands forecast trends and optimize inventory management, reducing unsold stock. However, challenges such as high implementation costs, lack of technical expertise, and concerns about data privacy remain significant barriers to AI adoption, particularly for smaller fashion brands. Additionally, consumer skepticism regarding AI-driven decision-making affects trust and engagement. This study suggests that fashion brands in Northern India must invest in AI-driven marketing tools, ensure transparency in AI applications, and align strategies with cultural preferences to enhance customer experiences. Government initiatives and collaborations with AI technology providers could support smaller brands in overcoming financial barriers. Addressing these challenges effectively will enable fashion companies to harness AI’s full potential in reshaping marketing communication and driving business growth.