Generative AI Trip Planner: Transforming Digital Travel Planning Through Large Language Models
Generative AI Trip Planner: Transforming Digital Travel Planning Through Large Language Models
Dr. Anita Sachin Mahajan and Vaishali Yashwant Pat
TLDR
This study demonstrates that AI-powered trip planners automate itinerary creation, provide personalized recommendations, and reduce planning time by 65-70% compared to traditional methods.
Abstract
The travel industry is undergoing a significant transformation driven by generative artificial intelligence (AI) technologies. This research paper presents a comprehensive analysis of generative AI trip planning systems, examining their architecture, capabilities, and impact on the travel planning experience. Through systematic literature review and empirical analysis, this study demonstrates that AI-powered trip planners automate itinerary creation, provide personalized recommendations, and reduce planning time by 65-70% compared to traditional methods [1]. The research evaluates current implementations including ChatGPT-based planners, LLM-driven applications, and multi-agent systems. Key findings indicate that 40% of leisure travelers worldwide now use AI tools for trip planning, with highest adoption among younger demographics and elite loyalty members [2]. The paper presents architectural frameworks, performance metrics, and user satisfaction results, establishing AI trip planners as transformative technology in the travel sector.