Machine Learning In Travel Market CAGR to be at 17.6% from 2025 to 2029 | $7.21 Billion Industry Revenue by 2029

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The Business Research Company's Machine Learning In Travel Global Market Report 2025 – Market Size, Trends, And Global Forecast 2025-2034

LONDON, GREATER LONDON, UNITED KINGDOM, December 3, 2025 /EINPresswire.com/ -- What Is The Projected Market Size & Growth Rate Of The Machine Learning In Travel Market?
The size of the machine learning sector within the travel market has expanded significantly in recent times. It is projected to increase from $3.21 billion in 2024 to $3.78 billion in 2025, with a compound annual growth rate (CAGR) of 17.9%. The growth during the historic period can be traced back to the escalating use of AI-based travel assistants, an increase in the use of predictive analytics for demand forecasting, a surge in integrating chatbots for customer assistance, an expansion in personal tailored travel advice, and rising automation in reservation and pricing systems.

In the coming years, the machine learning segment within the travel market is predicted to experience rapid growth. It is set to expand to a value of $7.22 billion by 2029, growing at a compound annual growth rate (CAGR) of 17.6%. This growth during the forecast period is primarily due to increased machine learning application for fraud detection, the surge in the use of AI for dynamic pricing, a heightened usage of sentiment analysis tools for measuring traveler feedback, a rise in data-informed decision-making by travel industries, and a higher amount of AI utilization for the optimization of routes and schedules. The forecast period is likely to see trends such as improved generative AI for personalized travel planning, the creation of autonomous travel management systems, innovation in real-time language translation with AI, advancements in predictive upkeep for travel infrastructure and the growth of AI-driven virtual travel assistant technology.

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What Is The Crucial Factor Driving The Global Machine Learning In Travel Market?
In the coming years, the machine learning segment within the travel market is predicted to experience rapid growth. It is set to expand to a value of $7.22 billion by 2029, growing at a compound annual growth rate (CAGR) of 17.6%. This growth during the forecast period is primarily due to increased machine learning application for fraud detection, the surge in the use of AI for dynamic pricing, a heightened usage of sentiment analysis tools for measuring traveler feedback, a rise in data-informed decision-making by travel industries, and a higher amount of AI utilization for the optimization of routes and schedules. The forecast period is likely to see trends such as improved generative AI for personalized travel planning, the creation of autonomous travel management systems, innovation in real-time language translation with AI, advancements in predictive upkeep for travel infrastructure and the growth of AI-driven virtual travel assistant technology.

Who Are The Emerging Players In The Machine Learning In Travel Market?
Major players in the Machine Learning In Travel Global Market Report 2025 include:
• Amazon.com Inc.
• Microsoft Corporation
• Hitachi Ltd.
• Accenture plc
• International Business Machines Corporation
• Oracle Corporation
• Salesforce Inc.
• SAP SE
• Tata Consultancy Services Limited
• NEC Corporation

What Are The Major Trends That Will Shape The Machine Learning In Travel Market In The Future?
Leading corporations in the machine learning in travel industry have shifted their attention towards creating innovative products like agentic AI solutions. These enhancements are aimed at boosting customer involvement, smooth operations, and customized travel experiences. Agentic AI solutions constitute sophisticated artificial intelligence mechanisms that can make autonomous choices and adapt behavior with minimal human interference to achieve their objectives effectively. For instance, Sabre Corporation, a tech company based in the US, in September 2025, rolled out a series of agentic AI-compatible APIs driven by its exclusive Model Context Protocol (MCP) server. Incorporated into the SabreMosaic platform and backed by the Sabre IQ layer that utilizes over 50 petabytes of travel data, these APIs allow travel companies to link their AI systems for immediate shopping, reservation, and post-reservation proceedings for airlines and hotels. This progress illustrates the practical implementation of agentic AI in automating intricate travel procedures and offering personalized, streamlined experiences for agencies and their customers.

What Segments Are Covered In The Machine Learning In Travel Market Report?
The machine learning in travel market covered in this report is segmented –

1) By Component: Software, Hardware, Services
2) By Deployment Mode: On-Premises, Cloud
3) By Application: Personalized Recommendations, Dynamic Pricing, Fraud Detection, Customer Service, Predictive Analytics, Other Applications
4) By End-User: Travel Agencies, Airlines, Car Rental Companies, Online Travel Platforms, Other End-Users

Subsegments:
1) By Software: Artificial Intelligence Platforms, Predictive Analytics Tools, Data Management Solutions, Machine Learning Frameworks, Natural Language Processing Tools
2) By Hardware: Servers, Storage Devices, Graphics Processing Units, Network Equipment, Edge Computing Devices
3) By Services: Professional Services, Managed Services, Consulting Services, Training And Support Services, System Integration Services

View the full machine learning in travel market report:
https://www.thebusinessresearchcompany.com/report/machine-learning-in-travel-global-market-report

Which Region Is Projected To Hold The Largest Market Share In The Global Machine Learning In Travel Market?
In the 2025 Global Market Report for Machine Learning in Travel, North America held the dominant position in 2024. Nevertheless, Asia-Pacific is projected to outpace other regions and become the fastest-growing one within the forecast period. The comprehensive report encompasses various regions including Asia-Pacific, Western Europe, Eastern Europe, North America, South America, the Middle East, and Africa.

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