Machine Learning In Travel Global Market Report 2025

Description

Machine learning in the travel industry involves the application of advanced algorithms and data-driven models to process and analyze large volumes of travel-related information, identify patterns, and generate intelligent predictions or automated decisions without the need for explicit programming. It enables travel companies to better understand customer behavior, optimize pricing strategies, forecast travel demand, enhance operational efficiency, and deliver personalized experiences to travelers.

The key components of machine learning in travel include software, hardware, and services. This technology utilizes artificial intelligence and data analytics to improve travel operations, enhance customer experiences, and support strategic business decision-making. Deployment modes include on-premises and cloud-based solutions. Core applications encompass personalized recommendations, dynamic pricing, fraud detection, customer service optimization, and predictive analytics. The primary end users include travel agencies, airlines, car rental companies, online travel platforms, and other organizations operating within the travel ecosystem.

Note that the outlook for this market is being affected by rapid changes in trade relations and tariffs globally. The report will be updated prior to delivery to reflect the latest status, including revised forecasts and quantified impact analysis. The report's Recommendations and Conclusions sections will be updated to give strategies for entities dealing with the fast-moving international environment.

The rapid escalation of U.S. tariffs and the resulting trade tensions in spring 2025 are significantly impacting the information technology sector, particularly in hardware manufacturing, data infrastructure, and software deployment. Higher duties on imported semiconductors, circuit boards, and networking equipment have raised production and operational costs for tech firms, cloud service providers, and data centers. Companies relying on globally sourced components for laptops, servers, and consumer electronics are facing longer lead times and increased pricing pressures. In parallel, tariffs on specialized software tools and retaliatory measures from key international markets have disrupted global IT supply chains and reduced overseas demand for U.S.-developed technologies. To navigate these challenges, the sector is accelerating investments in domestic chip fabrication, diversifying supplier bases, and adopting AI-driven automation to enhance operational resilience and cost efficiency.

The machine learning in travel market research report is one of a series of new reports from The Business Research Company that provides machine learning in travel market statistics, including machine learning in travel industry global market size, regional shares, competitors with a machine learning in travel market share, detailed machine learning in travel market segments, market trends and opportunities, and any further data you may need to thrive in the machine learning in travel industry. This machine learning in travel market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The machine learning in the travel market size has grown rapidly in recent years. It will grow from $3.21 billion in 2024 to $3.78 billion in 2025 at a compound annual growth rate (CAGR) of 17.9%. The growth in the historic period can be attributed to the increasing adoption of AI-based travel assistants, the growing use of predictive analytics for demand forecasting, the rising integration of chatbots for customer support, the increasing personalization in travel recommendations, and the growing automation in booking and pricing systems.

The machine learning in the travel market size is expected to see rapid growth in the next few years. It will grow to $7.22 billion in 2029 at a compound annual growth rate (CAGR) of 17.6%. The growth in the forecast period can be attributed to the rising use of machine learning for fraud detection, the growing implementation of AI in dynamic pricing, the increasing deployment of sentiment analysis tools for traveler feedback, the rise in data-driven decision-making by travel companies, and the growing utilization of AI for route and schedule optimization. Key trends in the forecast period include advancements in generative AI for personalized trip planning, the development of autonomous travel management systems, innovations in real-time language translation using AI, advancements in predictive maintenance for travel infrastructure, and the development of AI-driven virtual travel assistants.

The surge in demand for personalized customer experiences is fueling the growth of the market due to increasing customer expectations for tailored interactions. The growing demand for personalized customer experiences is expected to propel the growth of machine learning in the travel market going forward. Personalized customer experiences involve tailoring interactions and services to meet individual preferences and needs through data-driven insights that deliver relevant and engaging experiences across touchpoints. This demand is increasing as customers become more digitally connected and expect brands to understand their preferences and provide customized solutions. Machine learning in travel enables such personalization by analyzing traveler data and behavior to offer tailored recommendations, dynamic pricing, and customized services that enhance satisfaction and engagement throughout the journey. For instance, in January 2023, according to a report published by Marketing Tech News, a UK-based publishing company, about 66% of travelers globally preferred receiving personalized offers when booking trips, and around 61% of consumers worldwide were willing to pay extra for tailored travel experiences. Therefore, the growing demand for personalized customer experiences is expected to drive the growth of machine learning in the travel market.

Major companies operating in the machine learning in travel market are focusing on advancements in agentic AI solutions to enhance customer engagement, operational efficiency, and personalized travel experiences. Agentic AI solutions are advanced artificial intelligence systems capable of autonomous decision-making and adaptive behavior with minimal human intervention to achieve desired outcomes effectively. For instance, in September 2025, Sabre Corporation, a US-based technology company, launched a set of agentic AI-ready APIs powered by its proprietary Model Context Protocol (MCP) server. Integrated into the SabreMosaic platform and supported by the Sabre IQ layer leveraging over 50 petabytes of travel data, these APIs enable travel agencies to connect their AI systems for real-time shopping, booking, and post-booking workflows for flights and hotels. This innovation highlights the growing application of agentic AI in automating complex travel processes and delivering seamless, personalized experiences for agencies and customers.

In April 2023, Navan, Inc., a US-based technology company, acquired Tripeur for an undisclosed amount. This acquisition aimed to strengthen Navan's presence in the Indian business travel market by integrating Tripeur's advanced travel and expense management platform. It enhances Navan's localized offerings, leverages Tripeur's AI-driven automation capabilities, and provides a seamless, end-to-end travel experience for enterprises in the region. Tripeur is an India-based corporate travel management platform that provides machine learning solutions in the travel industry.

Major players in the machine learning in travel market are 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, Booking Holdings Inc., Tencent Holdings Limited , Infosys Limited, DXC Technology Company, Expedia Group Inc., Wipro Limited, Trip.com Group Limited, AMADEUS IT GROUP SOCIEDAD ANONIMA, LG CNS Co. Ltd., Sabre Corporation.

North America was the largest region in the machine learning in travel market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in machine learning in travel report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East and Africa.

The countries covered in the machine learning in travel market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The machine learning in travel market consists of revenues earned by entities by providing services such as revenue management services, voice and language translation services, automated customer segmentation services, operational efficiency and route optimization services, and automated baggage handling services. The market value includes the value of related goods sold by the service provider or contained within the service offering. The machine learning in the travel market also includes kayak AI platform, mindtrip, sabre travel AI, citymapper, and navan concierge. Values in this market are 'factory gate' values; that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

Machine Learning In Travel Global Market Report 2025 from The Business Research Company provides strategists, marketers and senior management with the critical information they need to assess the market.

This report focuses on machine learning in travel market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.

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Where is the largest and fastest growing market for machine learning in travel ? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The machine learning in travel market global report from the Business Research Company answers all these questions and many more.

The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market's historic and forecast market growth by geography.

The market characteristics section of the report defines and explains the market.
The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
The forecasts are made after considering the major factors currently impacting the market. These include:

The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.

Market segmentations break down the market into sub markets.
The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
The trends and strategies section analyses the shape of the market as it emerges from the crisis and suggests how companies can grow as the market recovers.

Scope

Markets Covered: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
Companies Mentioned: 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; Booking Holdings Inc.; Tencent Holdings Limited ; Infosys Limited; DXC Technology Company; Expedia Group Inc.; Wipro Limited; Trip.com Group Limited; AMADEUS IT GROUP SOCIEDAD ANONIMA; LG CNS Co. Ltd.; Sabre Corporation
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
Regions: Asia-Pacific; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita,
Data Segmentations: country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: PDF, Word and Excel Data Dashboard.

Product Code: r39704

1. Executive Summary

2. Machine Learning In Travel Market Characteristics

3. Machine Learning In Travel Market Trends And Strategies

4. Machine Learning In Travel Market - Macro Economic Scenario Including The Impact Of Interest Rates, Inflation, Geopolitics, Trade Wars and Tariffs, And Covid And Recovery On The Market

4.1. Supply Chain Impact from Tariff War & Trade Protectionism

5. Global Machine Learning In Travel Growth Analysis And Strategic Analysis Framework

5.1. Global Machine Learning In Travel PESTEL Analysis (Political, Social, Technological, Environmental and Legal Factors, Drivers and Restraints)
5.2. Analysis Of End Use Industries
5.3. Global Machine Learning In Travel Market Growth Rate Analysis
5.4. Global Machine Learning In Travel Historic Market Size and Growth, 2019 - 2024, Value ($ Billion)
5.5. Global Machine Learning In Travel Forecast Market Size and Growth, 2024 - 2029, 2034F, Value ($ Billion)
5.6. Global Machine Learning In Travel Total Addressable Market (TAM)

6. Machine Learning In Travel Market Segmentation

6.1. Global Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
Software
Hardware
Services
6.2. Global Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
On-Premises
Cloud
6.3. Global Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
Personalized Recommendations
Dynamic Pricing
Fraud Detection
Customer Service
Predictive Analytics
Other Applications
6.4. Global Machine Learning In Travel Market, Segmentation By End-User, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
Travel Agencies
Airlines
Hotels
Car Rental Companies
Online Travel Platforms
Other End-Users
6.5. Global Machine Learning In Travel Market, Sub-Segmentation Of Software, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
Artificial Intelligence Platforms
Predictive Analytics Tools
Data Management Solutions
Machine Learning Frameworks
Natural Language Processing Tools
6.6. Global Machine Learning In Travel Market, Sub-Segmentation Of Hardware, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
Servers
Storage Devices
Graphics Processing Units
Network Equipment
Edge Computing Devices
6.7. Global Machine Learning In Travel Market, Sub-Segmentation Of Services, By Type, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
Professional Services
Managed Services
Consulting Services
Training And Support Services
System Integration Services

7. Machine Learning In Travel Market Regional And Country Analysis

7.1. Global Machine Learning In Travel Market, Split By Region, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
7.2. Global Machine Learning In Travel Market, Split By Country, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

8. Asia-Pacific Machine Learning In Travel Market

8.1. Asia-Pacific Machine Learning In Travel Market Overview
Region Information, Market Information, Background Information, Government Initiatives, Regulations, Regulatory Bodies, Major Associations, Taxes Levied, Corporate Tax Structure, Investments, Major Companies
8.2. Asia-Pacific Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
8.3. Asia-Pacific Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
8.4. Asia-Pacific Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

9. China Machine Learning In Travel Market

9.1. China Machine Learning In Travel Market Overview
9.2. China Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
9.3. China Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion
9.4. China Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F,$ Billion

10. India Machine Learning In Travel Market

10.1. India Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
10.2. India Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
10.3. India Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

11. Japan Machine Learning In Travel Market

11.1. Japan Machine Learning In Travel Market Overview
11.2. Japan Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
11.3. Japan Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
11.4. Japan Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

12. Australia Machine Learning In Travel Market

12.1. Australia Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
12.2. Australia Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
12.3. Australia Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

13. Indonesia Machine Learning In Travel Market

13.1. Indonesia Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
13.2. Indonesia Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
13.3. Indonesia Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

14. South Korea Machine Learning In Travel Market

14.1. South Korea Machine Learning In Travel Market Overview
14.2. South Korea Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
14.3. South Korea Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
14.4. South Korea Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

15. Western Europe Machine Learning In Travel Market

15.1. Western Europe Machine Learning In Travel Market Overview
15.2. Western Europe Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
15.3. Western Europe Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
15.4. Western Europe Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

16. UK Machine Learning In Travel Market

16.1. UK Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
16.2. UK Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
16.3. UK Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

17. Germany Machine Learning In Travel Market

17.1. Germany Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
17.2. Germany Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
17.3. Germany Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

18. France Machine Learning In Travel Market

18.1. France Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
18.2. France Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
18.3. France Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

19. Italy Machine Learning In Travel Market

19.1. Italy Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
19.2. Italy Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
19.3. Italy Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

20. Spain Machine Learning In Travel Market

20.1. Spain Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
20.2. Spain Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
20.3. Spain Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

21. Eastern Europe Machine Learning In Travel Market

21.1. Eastern Europe Machine Learning In Travel Market Overview
21.2. Eastern Europe Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
21.3. Eastern Europe Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
21.4. Eastern Europe Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

22. Russia Machine Learning In Travel Market

22.1. Russia Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
22.2. Russia Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
22.3. Russia Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

23. North America Machine Learning In Travel Market

23.1. North America Machine Learning In Travel Market Overview
23.2. North America Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
23.3. North America Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
23.4. North America Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

24. USA Machine Learning In Travel Market

24.1. USA Machine Learning In Travel Market Overview
24.2. USA Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
24.3. USA Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
24.4. USA Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

25. Canada Machine Learning In Travel Market

25.1. Canada Machine Learning In Travel Market Overview
25.2. Canada Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
25.3. Canada Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
25.4. Canada Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

26. South America Machine Learning In Travel Market

26.1. South America Machine Learning In Travel Market Overview
26.2. South America Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
26.3. South America Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
26.4. South America Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

27. Brazil Machine Learning In Travel Market

27.1. Brazil Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
27.2. Brazil Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
27.3. Brazil Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

28. Middle East Machine Learning In Travel Market

28.1. Middle East Machine Learning In Travel Market Overview
28.2. Middle East Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
28.3. Middle East Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
28.4. Middle East Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

29. Africa Machine Learning In Travel Market

29.1. Africa Machine Learning In Travel Market Overview
29.2. Africa Machine Learning In Travel Market, Segmentation By Component, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
29.3. Africa Machine Learning In Travel Market, Segmentation By Deployment Mode, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion
29.4. Africa Machine Learning In Travel Market, Segmentation By Application, Historic and Forecast, 2019-2024, 2024-2029F, 2034F, $ Billion

30. Machine Learning In Travel Market Competitive Landscape And Company Profiles

30.1. Machine Learning In Travel Market Competitive Landscape
30.2. Machine Learning In Travel Market Company Profiles
- 30.2.1. Amazon.com Inc. Overview, Products and Services, Strategy and Financial Analysis
- 30.2.2. Microsoft Corporation Overview, Products and Services, Strategy and Financial Analysis
- 30.2.3. Hitachi Ltd. Overview, Products and Services, Strategy and Financial Analysis
- 30.2.4. Accenture plc Overview, Products and Services, Strategy and Financial Analysis
- 30.2.5. International Business Machines Corporation Overview, Products and Services, Strategy and Financial Analysis

31. Machine Learning In Travel Market Other Major And Innovative Companies

31.1. Oracle Corporation
31.2. Salesforce Inc.
31.3. SAP SE
31.4. Tata Consultancy Services Limited
31.5. NEC Corporation
31.6. Booking Holdings Inc.
31.7. Tencent Holdings Limited
31.8. Infosys Limited
31.9. DXC Technology Company
31.10. Expedia Group Inc.
31.11. Wipro Limited
31.12. Trip.com Group Limited
31.13. AMADEUS IT GROUP SOCIEDAD ANONIMA
31.14. LG CNS Co. Ltd.
31.15. Sabre Corporation

32. Global Machine Learning In Travel Market Competitive Benchmarking And Dashboard

33. Key Mergers And Acquisitions In The Machine Learning In Travel Market

34. Recent Developments In The Machine Learning In Travel Market

35. Machine Learning In Travel Market High Potential Countries, Segments and Strategies

35.1 Machine Learning In Travel Market In 2029 - Countries Offering Most New Opportunities
35.2 Machine Learning In Travel Market In 2029 - Segments Offering Most New Opportunities
35.3 Machine Learning In Travel Market In 2029 - Growth Strategies
- 35.3.1 Market Trend Based Strategies
- 35.3.2 Competitor Strategies

36. Appendix

36.1. Abbreviations
36.2. Currencies
36.3. Historic And Forecast Inflation Rates
36.4. Research Inquiries
36.5. The Business Research Company
36.6. Copyright And Disclaimer