ICT

Generative AI in Travel Market Size to Worth US$ 3,581.95 Million By 2032

According to the new research report published by Precedence Research, titled “Generative AI in Travel Market (By Type: Air Travel, Rail Travel, Cruise Travel; By Service Type: Accommodation Services, Transportation Services; By Deployment: Cloud-Based Model, On-Premises, Hybrid Model) – Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032 (By Product: Traditional, Advanced; By Application: Pottery, Tiles, Abrasives, Sanitary wave, Bricks & pipes, Others; By End User: Medical, Industrial, Building & Construction, Others) – Global Industry Analysis, Size, Share, Growth, Trends, Regional Outlook, and Forecast 2023-2032”, the global generative AI in travel market size is expected to be worth around US$ 3,581.95 million by 2032 and is poised to record a yearly growth rate of 18.94% from 2023 to 2032. The study investigates several elements and their consequences on the growth of the all-wheel drive market.

This report focuses on generative AI in travel market volume and value at the global level, regional level and company level. From a global perspective, this report represents the overall generative AI in travel market size by analysing historical data and future prospects. Regionally, this report focuses on several key regions: North America, Europe, the Middle East & Africa, Latin America, etc.

Generative AI in Travel Market Size 2023 To 2032

Key Takeaways:

  • North America dominated the market with the highest market share in 2022.
  • Asia Pacific is expected to hold a significant market share during the anticipated period.
  • By type, the air travel segment dominated the market with the largest market share in 2022. Additionally, the rail travel segment is expected to grow at a significant rate during the forecast period.
  • By service type, the accommodation services segment dominated the market with the largest market share in 2022. Additionally, the transportation accommodation segment is expected to grow at a noticeable rate during the forecast period.
  • By deployment, the cloud-based segment dominated the market with the highest market share in 2022. While on-premises deployment is expected to hold a lucrative market share during the predicted timeframe.

The research report includes specific segments by region (country), by company, by all segments. This study provides information about the growth and revenue during the historic and forecasted period of 2017 to 2032. Understanding the segments helps in identifying the importance of different factors that aid the market growth.

Download a Free Copy of Our Latest Sample Report@ https://www.precedenceresearch.com/sample/3118

The study also provides important advancements in organic and inorganic growth strategies in the worldwide generative AI in travel market. A lot of corporations are prioritizing new launches, product approvals, and other business expansion techniques. In addition, the report offers profiles of generative AI in travel market firms and market strategies. Furthermore, the research focuses on top industry participants, providing information such as company profiles, components and services offered, recent financial data, and key developments.

Generative AI in Travel Market  Report Scope

Report Coverage Details
Market Size in 2023 USD 751.91 Million
Market Size by 2032 USD 3,581.95 Million
Growth Rate from 2023 to 2032 CAGR of 18.94%
Largest Market North America
Base Year 2022
Forecast Period 2023 To 2032
Segments Covered By Type, By Service Type, and By Deployment
Regions Covered North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa

Also read: Generative AI in Real Estate Market Size to Worth US$ 1,047 Million By 2032

Major Key Points Covered in Report:

Executive Summary: It includes key trends of the electric vehicle fuel cell market related to products, applications, and other crucial factors. It also provides analysis of the competitive landscape and CAGR and market size of the electric vehicle fuel cell market based on production and revenue.

Production and Consumption by Region: It covers all regional markets to which the research study relates. Prices and key players in addition to production and consumption in each regional market are discussed.

Key Players: Here, the report throws light on financial ratios, pricing structure, production cost, gross profit, sales volume, revenue, and gross margin of leading and prominent companies competing in the Electric vehicle fuel cell market.

Market Segments: This part of the report discusses product, application and other segments of the electric vehicle fuel cell market based on market share, CAGR, market size, and various other factors.

Research Methodology: This section discusses the research methodology and approach used to prepare the report. It covers data triangulation, market breakdown, market size estimation, and research design and/or programs.

Market Key Players

Company profiles have been included in the report, which include essentials such as product portfolio, key strategies, along with all-inclusive SWOT analysis on each player. Company presence is mapped and presented through a matrix for all the prominent players, thus providing readers with actionable insights, which helps in thoughtfully presenting market status and predicting the competition level in the generative AI in travel market.

Some of the prominent players in the generative AI in travel market include

  • Amadeus IT Group
  • Google LLC
  • Airbnb Inc.
  • Expedia Group Inc.
  • Skyscanner Ltd.
  • Kayak Software Corporation
  • Sabre Corporation
  • Booking Holding Inc.

Generative AI in Travel Market Segmentations 

By Type

  • Air Travel
  • Rail Travel
  • Cruise Travel

By Service Type

  • Accommodation Services
  • Transportation Services

By Deployment

  • Cloud-Based Model
  • On-Premises
  • Hybrid Model

By Geography

  • North America
  • Europe
  • Asia-Pacific
  • Latin America
  • Middle East and Africa

Report Objectives 

  • To define, segment, and project the global market size for generative AI in travel market
  • To understand the structure of the market by identifying its various sub-segments
  • To provide detailed information about the key factors influencing the growth of the market (drivers, restraints, opportunities, and industry-specific challenges)
  • To analyse the micro-markets, with respect to individual growth trends, future prospects, and their contributions to the total market
  • To project the size of the market and its submarkets, in terms of value, with respect to global. (along with their respective key countries)
  • To profile key players and comprehensively analyse their core competencies
  • To understand the competitive landscape and identify major growth strategies adopted by players across the globe.
  • To analyse the competitive developments such as expansions & investments, new product launches, mergers & acquisitions, joint ventures, and agreements 

TABLE OF CONTENT

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology (Premium Insights)

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Generative AI in Travel Market 

5.1. COVID-19 Landscape: Generative AI in Travel Industry Impact

5.2. COVID 19 – Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

Chapter 6. Market Dynamics Analysis and Trends

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Generative AI in Travel Market, By Type

8.1. Generative AI in Travel Market, by Type, 2023-2032

8.1.1 Air Travel

8.1.1.1. Market Revenue and Forecast (2020-2032)

8.1.2. Rail Travel

8.1.2.1. Market Revenue and Forecast (2020-2032)

8.1.3. Cruise Travel

8.1.3.1. Market Revenue and Forecast (2020-2032)

Chapter 9. Global Generative AI in Travel Market, By Service Type

9.1. Generative AI in Travel Market, by Service Type, 2023-2032

9.1.1. Accommodation Services

9.1.1.1. Market Revenue and Forecast (2020-2032)

9.1.2. Transportation Services

9.1.2.1. Market Revenue and Forecast (2020-2032)

Chapter 10. Global Generative AI in Travel Market, By Deployment 

10.1. Generative AI in Travel Market, by Deployment, 2023-2032

10.1.1. Cloud-Based Model

10.1.1.1. Market Revenue and Forecast (2020-2032)

10.1.2. On-Premises

10.1.2.1. Market Revenue and Forecast (2020-2032)

10.1.3. Hybrid Model

10.1.3.1. Market Revenue and Forecast (2020-2032)

Chapter 11. Global Generative AI in Travel Market, Regional Estimates and Trend Forecast

11.1. North America

11.1.1. Market Revenue and Forecast, by Type (2020-2032)

11.1.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.1.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.1.4. U.S.

11.1.4.1. Market Revenue and Forecast, by Type (2020-2032)

11.1.4.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.1.4.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.1.5. Rest of North America

11.1.5.1. Market Revenue and Forecast, by Type (2020-2032)

11.1.5.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.1.5.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.2. Europe

11.2.1. Market Revenue and Forecast, by Type (2020-2032)

11.2.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.2.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.2.4. UK

11.2.4.1. Market Revenue and Forecast, by Type (2020-2032)

11.2.4.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.2.4.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.2.5. Germany

11.2.5.1. Market Revenue and Forecast, by Type (2020-2032)

11.2.5.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.2.5.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.2.6. France

11.2.6.1. Market Revenue and Forecast, by Type (2020-2032)

11.2.6.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.2.6.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.2.7. Rest of Europe

11.2.7.1. Market Revenue and Forecast, by Type (2020-2032)

11.2.7.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.2.7.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.3. APAC

11.3.1. Market Revenue and Forecast, by Type (2020-2032)

11.3.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.3.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.3.4. India

11.3.4.1. Market Revenue and Forecast, by Type (2020-2032)

11.3.4.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.3.4.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.3.5. China

11.3.5.1. Market Revenue and Forecast, by Type (2020-2032)

11.3.5.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.3.5.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.3.6. Japan

11.3.6.1. Market Revenue and Forecast, by Type (2020-2032)

11.3.6.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.3.6.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.3.7. Rest of APAC

11.3.7.1. Market Revenue and Forecast, by Type (2020-2032)

11.3.7.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.3.7.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.4. MEA

11.4.1. Market Revenue and Forecast, by Type (2020-2032)

11.4.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.4.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.4.4. GCC

11.4.4.1. Market Revenue and Forecast, by Type (2020-2032)

11.4.4.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.4.4.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.4.5. North Africa

11.4.5.1. Market Revenue and Forecast, by Type (2020-2032)

11.4.5.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.4.5.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.4.6. South Africa

11.4.6.1. Market Revenue and Forecast, by Type (2020-2032)

11.4.6.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.4.6.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.4.7. Rest of MEA

11.4.7.1. Market Revenue and Forecast, by Type (2020-2032)

11.4.7.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.4.7.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.5. Latin America

11.5.1. Market Revenue and Forecast, by Type (2020-2032)

11.5.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.5.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.5.4. Brazil

11.5.4.1. Market Revenue and Forecast, by Type (2020-2032)

11.5.4.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.5.4.3. Market Revenue and Forecast, by Deployment (2020-2032)

11.5.5. Rest of LATAM

11.5.5.1. Market Revenue and Forecast, by Type (2020-2032)

11.5.5.2. Market Revenue and Forecast, by Service Type (2020-2032)

11.5.5.3. Market Revenue and Forecast, by Deployment (2020-2032)

Chapter 12. Company Profiles

12.1. Amadeus IT Group

12.1.1. Company Overview

12.1.2. Product Offerings

12.1.3. Financial Performance

12.1.4. Recent Initiatives

12.2. Google LLC

12.2.1. Company Overview

12.2.2. Product Offerings

12.2.3. Financial Performance

12.2.4. Recent Initiatives

12.3. Airbnb Inc.

12.3.1. Company Overview

12.3.2. Product Offerings

12.3.3. Financial Performance

12.3.4. Recent Initiatives

12.4. Expedia Group Inc.

12.4.1. Company Overview

12.4.2. Product Offerings

12.4.3. Financial Performance

12.4.4. Recent Initiatives

12.5. Skyscanner Ltd.

12.5.1. Company Overview

12.5.2. Product Offerings

12.5.3. Financial Performance

12.5.4. Recent Initiatives

12.6. Kayak Software Corporation

12.6.1. Company Overview

12.6.2. Product Offerings

12.6.3. Financial Performance

12.6.4. Recent Initiatives

12.7. Sabre Corporation

12.7.1. Company Overview

12.7.2. Product Offerings

12.7.3. Financial Performance

12.7.4. Recent Initiatives

12.8. Booking Holding Inc.

12.8.1. Company Overview

12.8.2. Product Offerings

12.8.3. Financial Performance

12.8.4. Recent Initiatives

Chapter 13. Research Methodology

13.1. Primary Research

13.2. Secondary Research

13.3. Assumptions

Chapter 14. Appendix

14.1. About Us

14.2. Glossary of Terms

Why should you invest in this report?

If you are aiming to enter the global generative AI in travel market, this report is a comprehensive guide that provides crystal clear insights into this niche market. All the major application areas for generative AI in travel are covered in this report and information is given on the important regions of the world where this market is likely to boom during the forecast period of 2023-2030 so that you can plan your strategies to enter this market accordingly.

Besides, through this report, you can have a complete grasp of the level of competition you will be facing in this hugely competitive market and if you are an established player in this market already, this report will help you gauge the strategies that your competitors have adopted to stay as market leaders in this market. For new entrants to this market, the voluminous data provided in this report is invaluable.

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Prathamesh

I have completed my education in Bachelors in Computer Application. A focused learner having a keen interest in the field of digital marketing, SEO, SMM, and Google Analytics enthusiastic to learn new things along with building leadership skills.

Prathamesh

I have completed my education in Bachelors in Computer Application. A focused learner having a keen interest in the field of digital marketing, SEO, SMM, and Google Analytics enthusiastic to learn new things along with building leadership skills.

View all posts by Prathamesh →

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