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市场调查报告书
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1637952

2022-2032 年全球人工智慧在旅游和旅游市场规模研究（按组成部分、应用和区域预测） 到 2032 年，全球人工智慧在旅行和旅游市场将达到 16590.8 亿美元。

Global Artificial Intelligence in Travel and Tourism Market Size Study, by Components, by Application and Regional Forecasts 2022-2032
出版日期: | 出版商: Bizwit Research & Consulting LLP | 英文 285 Pages | 商品交期: 2-3个工作天内

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简介目录

2032年，全球人工智慧旅游市场规模将达到16,590.8亿美元。

2023年，全球旅游业人工智慧（AI）市场价值约为1099.2亿美元，预计2024年至2032年复合年增长率将达到35.20%，到2032年市场规模将达到16590.8亿美元。彻底改变服务的提供方式，透过分析大量资料集确保简化营运、增强客户体验并做出更好的决策。凭藉其自动化和客製化服务的能力，人工智慧已成为该行业不可或缺的一部分，推动创新和营运效率。

人工智慧技术正在重塑各行业的旅游业。预算提供者越来越多地利用自动化来提高成本效率，而优质旅游服务提供者则强调人性化的服务，以提供无缝、个人化的体验。机器学习演算法、预测分析和生成式人工智慧等先进的人工智慧功能使企业能够透过量身定制的建议和提高营运效率来满足客户的期望。

旅游业对科技的大量投资也推动了人工智慧采用的指数级成长。例如，人工智慧驱动的聊天机器人和虚拟助理正在帮助企业 24/7 管理客户查询，从而提高服务可靠性。这些技术使企业能够预测客户行为、优化定价策略并增强整体旅行体验。然而，资料隐私问题以及人工智慧解决方案与现有系统的整合等挑战可能会限制人工智慧的全面采用。

旅行和旅游市场人工智慧的区域动态凸显了其全球意义。由于航空公司、饭店和旅游平台等主要参与者对人工智慧技术的采用率很高，北美地区引领了市场。欧洲紧随其后，受益于政府鼓励旅游业数位转型的措施。同时，在数位化不断发展、旅行需求增加和人工智慧技术进步的推动下，亚太地区预计将呈现最快的成长。

目录

第 1 章：旅行与旅游业市场中的全球人工智慧执行摘要

  • 全球旅游业人工智慧市场规模及预测（2022-2032）
  • 区域概要
  • 分部摘要
    • 按组件分类
    • 按申请
  • 主要趋势
  • 经济衰退的影响
  • 分析师推荐与结论

第 2 章：全球人工智慧在旅行和旅游市场中的定义和研究假设

  • 研究目的
  • 市场定义
  • 研究假设
    • 包容与排除
    • 限制
    • 供给侧分析
      • 可用性
      • 基础设施
      • 监管环境
      • 市场竞争
      • 经济可行性（消费者的角度）
    • 需求面分析
      • 监理框架
      • 技术进步
      • 环境考虑
      • 消费者意识和接受度
  • 估算方法
  • 研究考虑的年份
  • 货币兑换率

第 3 章：全球人工智慧在旅游和旅游业市场动态中的应用

  • 市场驱动因素
    • 对自动化和个人化服务的需求不断增长
    • 对人工智慧技术的投资不断增加
    • 提高人工智慧应用程式的数据可用性
  • 市场挑战
    • 资料隐私问题
    • 与遗留系统的整合问题
  • 市场机会
    • 新兴市场的扩张
    • 人工智慧技术的进步
    • 越来越多采用生成式人工智慧

第 4 章：全球人工智慧在旅游业的应用分析

  • 波特的五力模型
    • 供应商的议价能力
    • 买家的议价能力
    • 新进入者的威胁
    • 替代品的威胁
    • 竞争竞争
    • 波特五力模型的影响分析
  • PESTEL分析
    • 政治的
    • 经济的
    • 社会的
    • 技术性
    • 环境的
    • 合法的
  • 顶级投资机会
  • 制胜策略
  • 人工智慧应用的颠覆性趋势
  • 分析师建议

第 5 章：全球旅游业人工智慧市场规模及预测：按组成部分（2022-2032 年）

  • 细分仪表板
  • 全球旅行和旅游业市场人工智慧：2022 年和 2032 年组件收入趋势分析
    • 先进的人工智慧能力
    • 自动化工具
    • 客户体验增强
    • 营运效率

第 6 章：全球旅游业人工智慧市场规模与预测：按应用分类（2022-2032 年）

  • 细分仪表板
  • 全球旅行和旅游市场人工智慧：2022 年和 2032 年应用收入趋势分析
    • 航空
    • 机场
    • 住宿
    • 运输

第 7 章：全球旅游业人工智慧市场规模及预测：按地区划分（2022-2032 年）

  • 北美洲
    • 我们
      • 组件细分（2022-2032）
      • 申请细目（2022-2032）
    • 加拿大
      • 组件细分（2022-2032）
      • 申请细目（2022-2032）
  • 欧洲
    • 英国
    • 德国
    • 法国
    • 西班牙
    • 义大利
    • 欧洲其他地区
  • 亚太地区
    • 中国
    • 印度
    • 日本
    • 澳洲
    • 韩国
    • 亚太地区其他地区
  • 拉丁美洲
    • 巴西
    • 墨西哥
    • 拉丁美洲其他地区
  • 中东和非洲
    • 沙乌地阿拉伯
    • 南非
    • 中东和非洲其他地区

第 8 章：竞争情报

  • 重点企业SWOT分析
    • Accor
    • Airbnb
    • Booking Holdings
  • 顶级市场策略
  • 公司简介
    • Accor
    • Airbnb
    • Booking Holdings
    • Delta Air Lines
    • Dubai Airports Company
    • easyJet
    • Expedia
    • Hopper
    • InterContinental Hotels Group
    • Marriott International
    • Turkish Airlines

第 9 章：研究过程

  • 研究方法
    • 资料探勘
    • 分析
    • 市场预测
    • 验证
    • 出版
  • 研究属性
简介目录

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