세계의 여행 및 관광 분야 인공지능 시장 규모 조사 : 구성요소별, 용도별, 지역별 예측(2022-2032년)

Global Artificial Intelligence in Travel and Tourism Market to reach USD 1659.08 billion by 2032.

The global Artificial Intelligence (AI) in Travel and Tourism Market was valued at approximately USD 109.92 billion in 2023 and is projected to experience a robust CAGR of 35.20% from 2024 to 2032, reaching a market size of USD 1659.08 billion by 2032. AI in travel and tourism is revolutionizing how services are delivered, ensuring streamlined operations, enhanced customer experiences, and better decision-making through the analysis of vast data sets. With its ability to automate and customize services, AI has become indispensable in this industry, driving innovation and operational efficiency.

AI technologies are reshaping travel operations across various sectors. Budget providers are increasingly leveraging automation for cost efficiencies, while premium travel service providers emphasize the human touch for a seamless, personalized experience. Advanced AI capabilities, such as machine learning algorithms, predictive analytics, and generative AI, are enabling businesses to meet customer expectations through tailored recommendations and improved operational efficiency.

The exponential growth in AI adoption is also fueled by significant investments in the technology across travel sectors. For example, AI-powered chatbots and virtual assistants are helping businesses manage customer inquiries 24/7, thus improving service reliability. These technologies enable businesses to forecast customer behavior, optimize pricing strategies, and enhance overall travel experiences. However, challenges like data privacy concerns and the integration of AI solutions with existing systems may limit the full-scale adoption of AI.

Regional dynamics in the AI in travel and tourism market underscore its global significance. North America leads the market due to high adoption rates of AI technologies among key players, including airlines, hotels, and travel platforms. Europe follows closely, benefiting from government initiatives to encourage digital transformation in tourism. Meanwhile, Asia-Pacific is projected to exhibit the fastest growth, driven by rising digitalization, increased travel demand, and advancements in AI technologies.

Major market players included in this report are:

• Accor
• Airbnb
• Booking Holdings
• Delta Air Lines
• Dubai Airports Company
• easyJet
• Expedia
• Hopper
• InterContinental Hotels Group
• Marriott International
• Turkish Airlines
• Sabre Corporation
• Amadeus IT Group
• IBM Corporation
• Google LLC

The detailed segments and sub-segment of the market are explained below:

By Components

• Advanced AI Capabilities
• Automation Tools
• Customer Experience Enhancements
• Operational Efficiencies

By Application

• Airlines
• Airports
• Lodging
• Transportation

By Region

• North America
  • U.S.
  • Canada
• Europe
  • UK
  • Germany
  • France
  • Spain
  • Italy
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • Australia
  • South Korea
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• Middle East & Africa
  • Saudi Arabia
  • South Africa
  • Rest of MEA

Years considered for the study are as follows:

• Historical year - 2022
• Base year - 2023
• Forecast period - 2024 to 2032

Key Takeaways:

• Market Estimates & Forecast for 10 years from 2022 to 2032.
• Annualized revenues and regional-level analysis for each market segment.
• Detailed analysis of the geographical landscape with country-level analysis of major regions.
• Competitive landscape with information on major players in the market.
• Analysis of key business strategies and recommendations on future market approaches.
• Analysis of the competitive structure of the market.
• Demand-side and supply-side analysis of the market.

Table of Contents

Chapter 1. Global Artificial Intelligence in Travel and Tourism Market Executive Summary

• 1.1. Global Artificial Intelligence in Travel and Tourism Market Size & Forecast (2022-2032)
• 1.2. Regional Summary
• 1.3. Segmental Summary
  • 1.3.1. By Components
  • 1.3.2. By Application
• 1.4. Key Trends
• 1.5. Recession Impact
• 1.6. Analyst Recommendation & Conclusion

Chapter 2. Global Artificial Intelligence in Travel and Tourism Market Definition and Research Assumptions

• 2.1. Research Objective
• 2.2. Market Definition
• 2.3. Research Assumptions
  • 2.3.1. Inclusion & Exclusion
  • 2.3.2. Limitations
  • 2.3.3. Supply Side Analysis
    • 2.3.3.1. Availability
    • 2.3.3.2. Infrastructure
    • 2.3.3.3. Regulatory Environment
    • 2.3.3.4. Market Competition
    • 2.3.3.5. Economic Viability (Consumer's Perspective)
  • 2.3.4. Demand Side Analysis
    • 2.3.4.1. Regulatory Frameworks
    • 2.3.4.2. Technological Advancements
    • 2.3.4.3. Environmental Considerations
    • 2.3.4.4. Consumer Awareness & Acceptance
• 2.4. Estimation Methodology
• 2.5. Years Considered for the Study
• 2.6. Currency Conversion Rates

Chapter 3. Global Artificial Intelligence in Travel and Tourism Market Dynamics

• 3.1. Market Drivers
  • 3.1.1. Rising Demand for Automated and Personalized Services
  • 3.1.2. Growing Investments in AI Technologies
  • 3.1.3. Increased Data Availability for AI Applications
• 3.2. Market Challenges
  • 3.2.1. Data Privacy Concerns
  • 3.2.2. Integration Issues with Legacy Systems
• 3.3. Market Opportunities
  • 3.3.1. Expansion in Emerging Markets
  • 3.3.2. Advancements in AI Technologies
  • 3.3.3. Increasing Adoption of Generative AI

Chapter 4. Global Artificial Intelligence in Travel and Tourism Industry Analysis

• 4.1. Porter's Five Forces Model
  • 4.1.1. Bargaining Power of Suppliers
  • 4.1.2. Bargaining Power of Buyers
  • 4.1.3. Threat of New Entrants
  • 4.1.4. Threat of Substitutes
  • 4.1.5. Competitive Rivalry
  • 4.1.6. Impact Analysis of Porter's Five Forces Model
• 4.2. PESTEL Analysis
  • 4.2.1. Political
  • 4.2.2. Economic
  • 4.2.3. Social
  • 4.2.4. Technological
  • 4.2.5. Environmental
  • 4.2.6. Legal
• 4.3. Top Investment Opportunities
• 4.4. Winning Strategies
• 4.5. Disruptive Trends in AI Applications
• 4.6. Analyst Recommendations

Chapter 5. Global Artificial Intelligence in Travel and Tourism Market Size & Forecasts by Components (2022-2032)

• 5.1. Segment Dashboard
• 5.2. Global Artificial Intelligence in Travel and Tourism Market: Component Revenue Trend Analysis, 2022 & 2032 (USD Billion)
  • 5.2.1. Advanced AI Capabilities
  • 5.2.2. Automation Tools
  • 5.2.3. Customer Experience Enhancements
  • 5.2.4. Operational Efficiencies

Chapter 6. Global Artificial Intelligence in Travel and Tourism Market Size & Forecasts by Application (2022-2032)

• 6.1. Segment Dashboard
• 6.2. Global Artificial Intelligence in Travel and Tourism Market: Application Revenue Trend Analysis, 2022 & 2032 (USD Billion)
  • 6.2.1. Airlines
  • 6.2.2. Airports
  • 6.2.3. Lodging
  • 6.2.4. Transportation

Chapter 7. Global Artificial Intelligence in Travel and Tourism Market Size & Forecasts by Region (2022-2032)

• 7.1. North America
  • 7.1.1. U.S.
    • 7.1.1.1. Component Breakdown (2022-2032)
    • 7.1.1.2. Application Breakdown (2022-2032)
  • 7.1.2. Canada
    • 7.1.2.1. Component Breakdown (2022-2032)
    • 7.1.2.2. Application Breakdown (2022-2032)
• 7.2. Europe
  • 7.2.1. UK
  • 7.2.2. Germany
  • 7.2.3. France
  • 7.2.4. Spain
  • 7.2.5. Italy
  • 7.2.6. Rest of Europe
• 7.3. Asia Pacific
  • 7.3.1. China
  • 7.3.2. India
  • 7.3.3. Japan
  • 7.3.4. Australia
  • 7.3.5. South Korea
  • 7.3.6. Rest of Asia Pacific
• 7.4. Latin America
  • 7.4.1. Brazil
  • 7.4.2. Mexico
  • 7.4.3. Rest of Latin America
• 7.5. Middle East & Africa
  • 7.5.1. Saudi Arabia
  • 7.5.2. South Africa
  • 7.5.3. Rest of Middle East & Africa

Chapter 8. Competitive Intelligence

• 8.1. Key Company SWOT Analysis
  • 8.1.1. Accor
  • 8.1.2. Airbnb
  • 8.1.3. Booking Holdings
• 8.2. Top Market Strategies
• 8.3. Company Profiles
  • 8.3.1. Accor
  • 8.3.2. Airbnb
  • 8.3.3. Booking Holdings
  • 8.3.4. Delta Air Lines
  • 8.3.5. Dubai Airports Company
  • 8.3.6. easyJet
  • 8.3.7. Expedia
  • 8.3.8. Hopper
  • 8.3.9. InterContinental Hotels Group
  • 8.3.10. Marriott International
  • 8.3.11. Turkish Airlines

Chapter 9. Research Process

• 9.1. Research Methodology
  • 9.1.1. Data Mining
  • 9.1.2. Analysis
  • 9.1.3. Market Estimation
  • 9.1.4. Validation
  • 9.1.5. Publishing
• 9.2. Research Attributes