The Latin America Artificial Intelligence in Tourism Market was valued at $93.7 Million in 2024 and projected to reach to $372.6 Million by 2029, representing a compound annual growth rate of 25.9%. Latin America's artificial intelligence in tourism market is positioned for substantial growth over the next five years, driven by increasing smartphone penetration, rising middle-class tourism demand, and growing investment in digital infrastructure across the region.
| Market Size in | USD 26.32 MN |
| Market Forecast in | |
| CAGR | |
| Forecast Period | |
| Units Considered | Value (USD MN) |
Latin America's AI in tourism market is growing at 25.9% CAGR, expanding from $93.7 million in 2024 to $372.6 million by 2029, driven by increasing digital transformation in the region's tourism sector.
Hotels, travel agencies, and tour operators across Latin America are adopting AI-driven chatbots, personalized recommendation engines, and automated booking systems to enhance customer experiences and operational efficiency.
Latin American countries are investing in digital tourism platforms and smart destination technologies, with AI playing a central role in customer service automation and data-driven decision-making.
Brazil ($120.2M) and Mexico ($107.3M) dominate the Latin American AI tourism market, accounting for the majority of regional adoption and investment in intelligent hospitality solutions.
| Report Metric | Details |
|---|---|
| Base Year | 2024 |
| Fastest Growing Segment | MANAGED SERVICES (Service) |
| Forecast Period | 2024-2029 |
| Growth Rate | CAGR of 28.7% from 2024 to 2029 |
| Largest Segment | EXTERNAL COMMUNICATION CHANNELS (Integration Mode) |
| Market Size Base Year (Billions) | ~USD 2.94 (2024) |
| Revenue Forecast (Billions) | ~USD 13.38 (2029) |
| Segments Covered | Offering, Travel Solution, Hospitality Solution, Service, Professional Service, Type, End User, Travel Industry, Hospitality Industry, Business Function, Integration Mode, Vertical, Deployment Type, Organization Size |
14 segment dimensions are covered across the global market.
| Country | 2025 size (native) |
|---|---|
| Brazil | USD 120.2 Million |
| Mexico | USD 107.3 Million |
| Argentina | USD 56.7 Million |
| Rest Of Latin America | USD 88.4 Million |
Latin America's AI in tourism market was valued at $93.7 million in 2024 and is projected to reach $372.6 million by 2029.
Latin America's AI in tourism market is growing at a compound annual growth rate (CAGR) of 25.9% from 2024 to 2029.
Latin America's tourism industry is increasingly adopting AI-powered chatbots, personalization engines, dynamic pricing tools, and destination marketing platforms.
Key drivers in Latin America include digital transformation initiatives, rising smartphone penetration, demand for enhanced customer experiences, and competitive pressures to modernize tourism operations.
By 2029, Latin America is expected to see widespread AI implementation across hospitality chains, travel agencies, and destination management organizations, with market value reaching $372.6 million.
This research study involved the extensive use of secondary sources, directories, and databases, such as Dun & Bradstreet (D&B) Hoovers and Bloomberg BusinessWeek, to identify and collect information useful for a technical, market-oriented, and commercial study of the AI in tourism market. The primary sources have been mainly industry experts from the core and related industries and preferred suppliers, manufacturers, distributors, service providers, technology developers, alliances, and organizations related to all segments of the value chain of this market. In-depth interviews have been conducted with various primary respondents, including key industry participants, subject matter experts, C-level executives of key market players, and industry consultants, to obtain and verify critical qualitative and quantitative information.
The market for companies offering AI in tourism solutions and services to different end users has been estimated and projected based on the secondary data made available through paid and unpaid sources and by analyzing their product portfolios in the ecosystem of the AI in tourism market. In the secondary research process, various sources such as Journal of Tourism Studies and Hospitality Research and International Journal of Contemporary Hospitality Management (IJCHM) have been referred to for identifying and collecting information for this study on the AI in tourism market. The secondary sources included annual reports, press releases, investor presentations of companies, white papers, journals, certified publications, and articles by recognized authors, directories, and databases. Secondary research has been mainly used to obtain essential information about the supply chain of the market, the total pool of key players, market classification, segmentation according to industry trends to the bottommost level, regional markets, and key developments from both market- and technology-oriented perspectives that primary sources have further validated.
In the primary research process, various primary sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief Experience Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and product development/innovation teams; related critical executives from AI in tourism service vendors, System Integrators, professional service providers, and industry associations; and key opinion leaders. Primary interviews were conducted to gather insights, such as market statistics, revenue data collected from services, market breakups, market size estimations, market forecasts, and data triangulation. Primary research also helped in understanding various trends related to technologies, applications, deployments, and regions. Stakeholders from the demand side, such as Chief Information Officers (CIOs), Chief Technology Officers (CTOs), Chief Strategy Officers (CSOs), and end users using AI in tourism services, were interviewed to understand the buyer’s perspective on suppliers, products, service providers, and their current usage of AI in tourism services which would impact the overall AI in tourism market.
Note: Others include sales managers, marketing managers, and product managers.
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Multiple approaches were adopted to estimate and forecast the size of the AI in tourism market. The first approach involves estimating market size by summing up the revenue generated by companies through the sale of AI in tourism solutions and services.
Both top-down and bottom-up approaches were used to estimate and validate the total size of the AI in tourism market. These methods were extensively used to estimate the size of various segments in the market. The research methodology used to estimate the market size includes the following:

After arriving at the overall market size, the AI in tourism market was divided into several segments and subsegments. The data was triangulated by studying various factors and trends from the demand and supply sides. Along with data triangulation and market breakdown, the market size was validated by the top-down and bottom-up approaches.
AI in the tourism refers to the use of artificial intelligence technologies in a variety of activities through which practices in travel, tourism, and hospitality are improved and optimized. It speaks about using solutions like machine learning, chatbots, predictive analytics, and automation to improve customer service, personalize travel experiences, streamline processes, and enhance efficiency in the whole industry. From personalized recommendations and dynamic pricing to real-time customer support and smart management of resources, AI is transforming all aspects of tourism businesses in their interactions with customers, management of services, and response to market needs.
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
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