Global AI in Hospitality and Tourism Market Size was valued at USD 2.9 Bn in 2024 and is predicted to reach USD 36.5 Bn by 2034 at a 28.9% CAGR during the forecast period for 2025-2034.
Artificial Intelligence (AI) in hospitality and tourism pertains to the utilization of AI technology to improve the overall experience, efficiency, and personalization in these industries. This involves using AI to manage operations, market, provide customer service, and analyze data, among other tasks. The hospitality and tourist industries may optimize their operations and spur growth by incorporating AI technologies, providing clients with more efficient, memorable, and personalized experiences. Visitors look for distinctive and customized experiences. AI assists in the analysis of consumer data to deliver personalized services and recommendations that increase customer loyalty and satisfaction.
The market growth is being driven by several factors including technological advancements, increasing demand for personalization, operational efficiency and cost reduction, enhanced customer service, integration of big data analytics and many others. However, high costs and privacy and security concerns are expected to hinder market growth during the forecast period.
The AI in hospitality and tourism market is segmented based on type, application, and end user. Based on type, the market is segmented as natural language processing, machine learning algorithms, computer vision and image recognition, chatbots and virtual assistants, recommendation systems and sentiment analysis. By application, the market is segmented into customer service and support, personalized marketing and advertising, hotel and room booking systems, virtual concierge services, smart guest room automation, data analytics and business intelligence and revenue management and pricing optimization. Based on end users, the industry is bifurcated into hotels and resorts, airlines and airports, travel agencies and tour operators, restaurants and food service providers, cruise lines and maritime tourism and online travel platforms and booking websites.
The chatbots and virtual assistants segment is expected to hold a major share of the global AI in hospitality and tourism market. Without requiring human assistance, chatbots and virtual assistants offer 24/7 customer support by managing questions, reservations, and other duties. This guarantees that visitors may get help whenever they need it, improving their entire experience. These artificial intelligence (AI) products are especially useful in the global hospitality and tourism sector where visitors come from a variety of linguistic backgrounds since they can be taught to understand and reply in numerous languages. The market is growing because of these uses.
Customer service and support are projected to grow at a rapid rate in the global AI in hospitality and tourism market. Artificial intelligence (AI)-powered customer support platforms may resolve typical problems including check-in information, cancellation rules, and booking revisions as well as frequently asked questions (FAQs) without requiring human assistance. AI may also prioritize and triage requests for more complicated problems, sending them to the right human agents and increasing the effectiveness of the customer care process.
The North America AI in hospitality and tourism market is expected to register the highest market share in terms of revenue in the near future. High adoption rates of AI technologies, a strong emphasis on improving customer experience, and sophisticated technological infrastructure are driving the industry's major expansion in North America's hotel and tourism sector. The area is home to numerous cutting-edge startups and top IT firms that are accelerating the adoption of AI in the travel and hospitality industries. In addition, Asia Pacific is projected to grow at a rapid rate in the global AI in hospitality and tourism market due to rapid digital transformation. Moreover, travel destinations in the Asia Pacific area are among the fastest growing in the globe, with China, Japan, Thailand, and Australia leading the way in terms of foreign visitor arrivals. The need for cutting-edge AI solutions to handle the growing number of tourists and improve their experiences is fueled by this growth.
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Report Attribute |
Specifications |
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Market Size Value In 2024 |
USD 2.9 Bn |
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Revenue Forecast In 2034 |
USD 36.5 Bn |
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Growth Rate CAGR |
CAGR of 28.9% from 2025 to 2034 |
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Quantitative Units |
Representation of revenue in US$ Bn and CAGR from 2025 to 2034 |
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Historic Year |
2021 to 2024 |
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Forecast Year |
2025-2034 |
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Report Coverage |
The forecast of revenue, the position of the company, the competitive market structure, growth prospects, and trends |
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Segments Covered |
By Type, By Application, By End-user and By Region |
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Regional Scope |
North America; Europe; Asia Pacific; Latin America; Middle East & Africa |
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Country Scope |
U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; France; Italy; Spain; South East Asia; South Korea |
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Competitive Landscape |
IBM Corporation, Google LLC, Amazon Web Services (AWS), Microsoft Corporation, Oracle Corporation, Salesforce.com, Inc., SAP SE, Intel Corporation, NVIDIA Corporation, Alibaba Group Holding Limited, Huawei Technologies Co., Ltd., Accenture PLC, Cisco Systems, Inc., Travelport Worldwide Limited, Amadeus IT Group S.A., Expedia Group, Inc., Airbnb, Inc., Tripadvisor, Inc., Booking Holdings Inc., Agoda Company Pte. Ltd., Ctrip.com International, Ltd., MakeMyTrip Limited, Kayak Software Corporation, Trivago N.V., and Others. |
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Customization Scope |
Free customization report with the procurement of the report and modifications to the regional and segment scope. Particular Geographic competitive landscape. |
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Pricing And Available Payment Methods |
Explore pricing alternatives that are customized to your particular study requirements. |
AI in Hospitality and Tourism Market- By Type
AI in Hospitality and Tourism Market- By Application
AI in Hospitality and Tourism Market- By End User
AI in Hospitality and Tourism Market- By Region
North America-
Europe-
Asia-Pacific-
Latin America-
Middle East & Africa-
InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.
Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.
Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.
Secondary research
The secondary research sources that are typically mentioned to include, but are not limited to:
The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista
Primary Research:
Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies
The contributors who typically take part in such a course include, but are not limited to:
Data Modeling and Analysis:
In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.
The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.
