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AI-Driven Marketing Automation: Boosting Guest Engagement

In: Proceedings of the 2nd International Conference on Innovation and Regenerative Trends in Tourism and Hospitality Industry (IRTTHI 2025)

Author

Listed:
  • Afshan Irshad

    (Chandigarh University, Research Scholar)

  • Ajit Kumar Singh

    (Chandigarh University, Professor)

Abstract

The research examines AI marketing automation systems in tourism to enhance visitor engagement while optimizing marketing strategies. The research evaluates how artificial intelligence technologies including predictive analytics and chatbots and natural language processing (NLP) enhance operational efficiency and simplify customer interactions and enable personalized marketing activities. The research used case studies of the Maldives and Bhutan within a qualitative framework to demonstrate how artificial intelligence affects travel marketing. The research demonstrates that artificial intelligence automation enables companies to deliver personalized experiences while improving operational efficiency and providing data-based insights to optimize marketing strategies. The implementation of artificial intelligence automation faces ongoing challenges because of ethical concerns and high costs and data privacy issues. The research identifies its limitations by requiring additional empirical evidence and depending on secondary data sources. The research investigates these elements to provide insights about future industrial applications while demonstrating artificial intelligence’s transformative impact on travel marketing.

Suggested Citation

  • Afshan Irshad & Ajit Kumar Singh, 2025. "AI-Driven Marketing Automation: Boosting Guest Engagement," Advances in Economics, Business and Management Research, in: Manish Sharma & Ajit Kumar Singh & Pankaj Tyagi (ed.), Proceedings of the 2nd International Conference on Innovation and Regenerative Trends in Tourism and Hospitality Industry (IRTTHI 2025), pages 66-73, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-799-1_7
    DOI: 10.2991/978-94-6463-799-1_7
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