Artificial Intelligence in Tourism Market by Solution (Virtual Assistant & Chatbots, Pricing & Revenue Management, Booking Management System), End Users (Maritime Travel, Aviation, Cruise Line Operators, Resorts & Theme Parks) - Global Forecast to 2030
관광 분야 AI 시장 규모는 2024년 29억 5,000만 달러, 2030년 133억 8,000만 달러로 추정되며, 연평균 성장률(CAGR)은 28.7%를 나타낼 것으로 예측됩니다.
AI는 주로 승차 공유와 셔틀버스를 통해 관광 분야의 모빌리티 솔루션을 크게 개선했습니다. 데이터 분석과 머신러닝 알고리즘은 교통 데이터의 실시간 분석과 가장 효율적인 경로를 따르는 차량의 과거 데이터를 기반으로 경로 선택을 최적화하여 이동 시간과 비용을 절감합니다. 대기 시간 단축과 정확한 도착 예측을 통해 더 나은 고객 경험을 제공하는 동시에 업무 효율성을 향상시킬 수 있습니다.
| 조사 범위 |
| 조사 대상 연도 |
2019-2030년 |
| 기준 연도 |
2024년 |
| 예측 기간 |
2024-2030년 |
| 검토 단위 |
미화(10억 달러) |
| 부문별 |
제품별, 유형별, 최종사용자별, 지역별 |
| 대상 지역 |
북미, 유럽, 아시아태평양, 중동/아프리카, 라틴아메리카 |
여행 예약 사이트에서 사용되는 알고리즘은 보다 맞춤화된 추천, 역동적인 가격 책정, 사용하기 쉬운 사용자 인터페이스로 이어져 사용자의 비교를 용이하게 하고 비교적 정보에 입각한 의사 결정을 내릴 수 있게 합니다. 또한, AI를 활용한 솔루션은 차량의 실시간 가동률과 예지보전에도 활용되고 있습니다. 해운업계에서는 크루즈 라인과 페리 서비스가 AI를 활용하여 항로 계획, 선상 경험, 그리고 분석을 통해 안전 시나리오의 가능성을 높이고 있습니다. 항공사는 챗봇을 통한 자동화된 고객 서비스를 통해 AI를 활용하고 있습니다. 항공편 최적화, 수하물 추적 및 기타 관련 업무는 모두 더 나은 경험을 제공하는 데 기여하고 있습니다. 이 밖에도 철도 및 도로 여행은 AI를 통해 스케줄링, 승객과의 소통, 강력한 안전 조치 시행에 활용하고 있으며, AI는 비즈니스 및 고객과의 관계 방식을 크게 변화시키고, 혁신하고, 관광 분야의 성장에 기여하고 있습니다.
관광 분야에서는 렌터카 및 모빌리티 제공업체와 같은 최종 사용자가 고객 서비스 경험과 효율성을 개선하기 위해 AI를 활용하는 사례가 늘고 있습니다. AI 기술을 통해 수요 예측을 통한 차량 관리, 차량 가동률 관리, 시장 상황에 따른 가격 전략의 자동화를 실현할 수 있으며, AI 기반의 다른 이점으로는 사용자 맞춤형 차량 선택, 경로, 원활하고 효율적인 이동을 위한 실시간 교통 정보 제공 등이 있습니다. 챗봇과 가상 비서를 통해 렌터카 업체는 즉각적인 고객 관리 지원을 제공하고, 모든 질문에 대한 답변을 제공하며, 운영 비용을 절감하고 예약할 수 있습니다. 원활한 모빌리티 솔루션에 대한 수요가 증가함에 따라, 렌터카 서비스에 AI를 통합함으로써 기업은 고객을 만족시킬 뿐만 아니라 빠르게 변화하는 시장에서 앞서나갈 수 있습니다.
싱가포르 창이공항은 현재 iFerret이라는 AI 시스템을 도입하여 활주로에서 쓰레기와 야생동물을 스캔하는 AI 시스템을 도입했습니다. 이 카메라는 고해상도로 4cm 크기의 작은 물체도 발견할 수 있으며, 2024년 말까지는 완전한 기능을 갖출 예정입니다. 서울시는 2023년 12월 메이데이 연휴에 서울을 찾는 외국인 관광객을 위해 두 가지 서비스를 시작했습니다. 특히 외국인이 이용하는 택시 배차 앱 '타보'와 지하철역 내 실시간 번역 서비스입니다. 타보 앱은 외국인이 쉽게 택시를 주문할 수 있는 앱이고, 번역 서비스는 주요 관광안내소에 설치된 AI와 음성문자화 기술을 적용해 한국어를 못하는 사람들의 실시간 대화에 대응합니다. 일본 정부는 5개 기업에 4억 7,000만 달러의 자금 지원을 승인했으며, 그 중 KDDI는 2024년 4월까지 방문객의 경험과 지속 가능한 관행을 개발하는 데 있어 관광 부문을 활용하는 방법을 더 많이 알리기 위해 AI 기술을 개발하고 있습니다. 이러한 개발은 향후 몇 년동안 아시아태평양의 유망한 성장에 기여할 것입니다.
이 보고서는 세계 관광 분야의 인공지능(AI) 시장을 조사했으며, 제공 제품별/유형별/최종 사용자별/지역별 동향, 시장 진출기업 프로파일 등을 정리한 보고서입니다.
목차
제1장 서론
제2장 조사 방법
제3장 주요 요약
제4장 프리미엄 인사이트
제5장 시장 개요와 업계 동향
- 서론
- 시장 역학
- 관광 AI 역사
- 생태계 분석
- 사례 연구 분석
- 공급망 분석
- 관세 및 규제 상황
- 가격 분석
- 기술 분석
- 특허 분석
- Porter의 Five Forces 분석
- 고객의 비즈니스에 영향을 미치는 동향/혼란
- 주요 이해관계자와 구입 기준
- 2025년 주요 컨퍼런스 및 이벤트
- 관광 분야 AI 시장 기술 로드맵
- 관광 분야 AI 시장 베스트 프랙티스
- 현재 비즈니스 모델과 새로운 비즈니스 모델
- 관광 분야 AI 시장 : 툴, 프레임워크, 테크닉
- 트레이드 분석
- 투자와 자금조달 시나리오
- 인공지능(AI)/생성형 AI가 관광업에 미치는 영향
제6장 관광 분야 AI 시장, 제공 제품별
제7장 관광 분야 AI 시장, 유형별
제8장 관광 분야 AI 시장, 최종사용자별
제9장 관광 분야 AI 시장, 지역별
- 서론
- 북미
- 유럽
- 유럽 : 거시경제 전망
- 영국
- 독일
- 프랑스
- 이탈리아
- 스페인
- 북유럽 국가
- 기타
- 아시아태평양
- 아시아태평양 : 거시경제 전망
- 중국
- 일본
- 인도
- 호주 및 뉴질랜드
- 한국
- ASEAN
- 기타
- 중동 및 아프리카
- 중동 및 아프리카 : 거시경제 전망
- 사우디아라비아
- 아랍에미리트(UAE)
- 쿠웨이트
- 카타르
- 남아프리카공화국
- 기타
- 라틴아메리카
- 라틴아메리카 : 거시경제 전망
- 브라질
- 멕시코
- 아르헨티나
- 기타
제10장 경쟁 구도
- 서론
- 주요 시장 진출기업의 전략/강점
- 시장 점유율 분석
- 매출 분석
- 기업 평가 매트릭스 : 주요 시장 진출기업, 2024년
- 기업 평가 매트릭스 : 스타트업/중소기업, 2024년
- 경쟁 시나리오와 동향
- 브랜드/제품 비교
- 관광 솔루션 제공업체 주요 AI 기업 평가와 재무 지표
제11장 기업 개요
- 주요 시장 진출기업
- SNOWFLAKE INC.
- SALESFORCE, INC.
- AMAZON WEB SERVICES, INC.
- IBM
- MICROSOFT CORPORATION, INC.
- NVIDIA CORPORATION
- SAS INSTITUTE
- SABRE CORPORATION
- HUAWEI
- (24)7.AI
- VIRTUSA CORPORATION
- APPIER INC.
- TRAVELPORT WORLDWIDE LTD
- AMADEUS IT GROUP, S.A.
- ZENDESK
- 스타트업/중소기업
- DEVOX SOFTWARE
- ALTEXSOFT
- JIO HAPTIK TECHNOLOGIES LIMITED
- SHR GROUP
- DUVE
- NEXSCIENT
- PERSADO
- CANARY TECHNOLOGIES
- MIZE
- FLYR
- GEOVEA
- LAYLA AI
제12장 인접 시장 및 관련 시장
제13장 부록
LSH
The AI in tourism market is estimated at USD 2.95 billion in 2024 and USD 13.38 billion in 2030 at a Compound Annual Growth Rate (CAGR) of 28.7%. AI has largely improved mobility solutions in the tourism sector, primarily through ridesharing and shuttles. Data analytics and machine learning algorithms optimize the choice of route based on real-time analysis of the traffic data and historical data on vehicles following the most efficient routes to reduce travel time and costs. It can improve operational efficiency, all the while offering the ability for better customer experiences by reducing waiting time and correct arrival estimates.
| Scope of the Report |
|---|
| Years Considered for the Study | 2019-2030 |
| Base Year | 2024 |
| Forecast Period | 2024-2030 |
| Units Considered | USD (Billion) |
| Segments | by offering (solutions and services), by type (Generative AI, other AI), by end user (travel industry, hospitality industry) |
| Regions covered | North America, Europe, Asia Pacific, Middle East & Africa, and Latin America. |
"By end user, travel industry segment to hold the largest market size during the forecast period."
Algorithms used by travel booking sites lead to more customized recommendations, dynamic pricing, and easier-to-use user interfaces that ease users' comparisons and allow them to make relatively well-informed decisions. It utilizes AI-driven solutions for providing real-time availability and predictive maintenance for its vehicles. In the maritime industries, cruise lines and ferry services use AI to enhance route planning, onboard experiences, and even the possibilities of a safety scenario through analytics. Airlines utilize AI through automated service to customers in the form of chatbots. Optimization of flights, tracking baggage, and other related things all contribute to a better-quality experience. Others include rail and road travel, using AI for scheduling, communicating with passengers, and implementing robust safety measures. AI plays a role in the deep transformation of businesses and how they interact with customers, innovation, and growth in the tourism sector.
"The car rental & mobility providers segment to register the fastest growth rate during the forecast period."
In the tourism sector, end users like car rental and mobility providers have increasingly used AI to improve experience and efficiency in customer services. Fleet management through demand prediction, vehicle availability management, and automation of pricing strategies depending on market conditions is achievable through AI technologies. Some of the other advantages of AI-based applications include providing users with tailored car picks, routes, and real-time traffic updates to make travel smooth and efficient. With AI chatbots and virtual assistants, automobile rental companies can be able to instantaneously provide customer care support, answer all possible questions, and be able to make a booking at reduced operating costs. With increased demand for a seamless mobility solution, AI integration into the car rental service will help companies satisfy their customers but also be ahead of the curve in such fast-moving markets.
"Asia Pacific to hold the highest market growth during the forecast period."
Singapore Changi Airport now has an AI system scanning its runways for debris and wildlife, called iFerret. The cameras come with high definition for the spotting of objects of as small a size of 4 cm. It will be fully functional by end 2024. The Seoul Metropolitan Government launched two services for the foreign visitors who began flocking to the city on the May Day holiday in December 2023. It includes taxi-hailing application, especially used by foreigners, called Tabo, and the real-time translation services at subway stations. The Tabe app is intended for easy ordering of taxis by foreigners, while the translation service will cater to real-time conversations among non-Korean-speaking people through application of AI and voice-to-text technology at major tourist information center. The Japanese government approved a funding of about USD 470 million to be granted to five companies, among them the KDDI Corporation is developing AI technology intended to further enlighten the country on how to leverage tourism sectors in developing visitor experiences and sustainable practices by April 2024. These developments contribute to the promising future growth of Asia Pacific region in the coming years.
In-depth interviews have been conducted with chief executive officers (CEOs), Directors, and other executives from various key organizations operating in the AI in tourism market.
- By Company Type: Tier 1 - 20%, Tier 2 - 50%, and Tier 3 - 30%
- By Designation: C-level -73%, D-level - 18%, and Others - 9%
- By Region: North America - 55%, Europe - 9%, Asia Pacific - 36%
The major players in the AI in tourism market include Snowflake (US), IBM (US), NVIDIA (US), Microsoft (US), AWS (US), Salesforce (US), Appier (Taiwan), Huawei (China), Sabre Corporation (US), SAS Institute (US), [24]7.ai (US), Virtusa Corporation (US), Travelport (UK), Amadeus (Spain), Devox Software (Poland) , AltexSoft (US), Jio Haptik Technologies Limited (India), SHR Group (US), Duve (US), Nexscient (US), Persado (US), Canary Technologies (US), Mize (US), FLYR (US), Geovea (US), Layla AI (Germany). These players have adopted various growth strategies, such as partnerships, agreements and collaborations, new product launches, enhancements, and acquisitions to expand their AI in tourism market footprint.
Research Coverage
The market study covers the AI in tourism market size across different segments. It aims at estimating the market size and the growth potential across various segments, including by offering (solutions and services) by type (Generative AI, other AI), by end user (travel industry, hospitality industry) and Region (North America, Europe, Asia Pacific, Middle East & Africa, and Latin America). The study includes an in-depth competitive analysis of the leading market players, their company profiles, key observations related to product and business offerings, recent developments, and market strategies.
Key Benefits of Buying the Report
The report will help the market leaders/new entrants with information on the closest approximations of the global AI in tourism market's revenue numbers and subsegments. This report will help stakeholders understand the competitive landscape and gain more insights to position their businesses better and plan suitable go-to-market strategies. Moreover, the report will provide insights for stakeholders to understand the market's pulse and provide them with information on key market drivers, restraints, challenges, and opportunities.
The report provides insights on the following pointers:
Analysis of key drivers (rising adoption of data automation tools to ease the decision-making process, rising demand for highly personalized services to enhance customer experience), restraints (high implementation costs), opportunities (incorporation of AI in areas of tourism revolutionizing customer interaction, emergence of AI-driven applications for flight forecasting), and challenges (concerns related to data privacy and security) influencing the growth of the AI in tourism market.
Product Development/Innovation: Detailed insights on upcoming technologies, research & development activities, and new product & service launches in the AI in tourism market.
Market Development: The report provides comprehensive information about lucrative markets and analyses the AI in tourism market across various regions.
Market Diversification: Exhaustive information about new products & services, untapped geographies, recent developments, and investments in the AI in tourism market.
Competitive Assessment: In-depth assessment of market shares, growth strategies and service offerings of leading include Snowflake (US), IBM (US), NVIDIA (US), Microsoft (US), AWS (US), Salesforce (US), Huawei (China), Sabre Corporation (US), SAS Institute (US), Appier (Taiwan), [24]7.ai (US), Virtusa Corporation (US), Travelport (UK), Amadeus (Spain), Devox Software (Poland) , AltexSoft (US), Jio Haptik Technologies Limited (India), SHR Group (US), Duve (US), Nexscient (US), Persado (US), Canary Technologies (US), Mize (US), FLYR (US), Geovea (US), Layla AI (Germany).
TABLE OF CONTENTS
1 INTRODUCTION
- 1.1 STUDY OBJECTIVES
- 1.2 MARKET DEFINITION
- 1.3 STUDY SCOPE
- 1.3.1 MARKET SEGMENTATION
- 1.3.2 INCLUSIONS & EXCLUSIONS
- 1.4 YEARS CONSIDERED
- 1.5 CURRENCY CONSIDERED
- 1.6 STAKEHOLDERS
2 RESEARCH METHODOLOGY
- 2.1 RESEARCH DATA
- 2.1.1 SECONDARY DATA
- 2.1.2 PRIMARY DATA
- 2.1.2.1 Primary interviews with experts
- 2.1.2.2 Breakdown of primary profiles
- 2.1.2.3 Key insights from industry experts
- 2.2 MARKET SIZE ESTIMATION
- 2.2.1 TOP-DOWN APPROACH
- 2.2.2 BOTTOM-UP APPROACH
- 2.2.3 AI IN TOURISM MARKET ESTIMATION: DEMAND-SIDE ANALYSIS
- 2.3 DATA TRIANGULATION
- 2.4 RISK ASSESSMENT
- 2.5 RESEARCH ASSUMPTIONS
- 2.6 RESEARCH LIMITATIONS
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
- 4.1 OPPORTUNITIES FOR KEY PLAYERS IN AI IN TOURISM MARKET
- 4.2 AI IN TOURISM MARKET, BY OFFERING
- 4.3 AI IN TOURISM MARKET, BY SERVICE
- 4.4 AI IN TOURISM MARKET, BY PROFESSIONAL SERVICE
- 4.5 AI IN TOURISM MARKET, BY TRAVEL SOLUTION
- 4.6 AI IN TOURISM MARKET, BY HOSPITALITY SOLUTION
- 4.7 AI IN TOURISM MARKET, BY END USERS IN TRAVEL INDUSTRY
- 4.8 AI IN TOURISM MARKET, BY END USERS IN HOSPITALITY INDUSTRY
- 4.9 AI IN TOURISM MARKET, BY TYPE
- 4.10 NORTH AMERICA: AI IN TOURISM MARKET, BY OFFERING AND END USER
5 MARKET OVERVIEW AND INDUSTRY TRENDS
- 5.1 INTRODUCTION
- 5.2 MARKET DYNAMICS
- 5.2.1 DRIVERS
- 5.2.1.1 Rising adoption of data automation tools to ease decision-making process
- 5.2.1.2 Increasing demand for highly personalized services to enhance customer experience
- 5.2.2 RESTRAINTS
- 5.2.2.1 High initial costs
- 5.2.3 OPPORTUNITIES
- 5.2.3.1 Incorporation of AI in areas of tourism revolutionizing customer interaction
- 5.2.3.2 Emergence of AI-driven applications for flight forecasting
- 5.2.4 CHALLENGES
- 5.2.4.1 Concerns related to data privacy and security
- 5.3 BRIEF HISTORY OF AI IN TOURISM
- 5.4 ECOSYSTEM ANALYSIS
- 5.5 CASE STUDY ANALYSIS
- 5.5.1 BOOKING.COM HELPS CUSTOMERS EXPERIENCE NEW WORLD OF TRAVEL USING AWS AND GENERATIVE AI
- 5.5.2 TRAVELPASS' JOURNEY TO DELIVER MORE CURATED TRAVELER EXPERIENCES - AT HALF COST
- 5.5.3 A1 INTELIGENCIA EM VIAGENS BOOSTS TEAM EFFICIENCY AND CUSTOMER EXPERIENCE WITH POWER AUTOMATE AND COPILOT STUDIO
- 5.5.4 HOMARIS ACHIEVED HIGHER GUEST SATISFACTION RATES WITH SMARTPRIORITY BY DUVEAI
- 5.6 SUPPLY CHAIN ANALYSIS
- 5.7 TARIFF AND REGULATORY LANDSCAPE
- 5.7.1 TARIFF RELATED TO PROCESSORS AND CONTROLLERS (HSN: 854231)
- 5.7.2 REGULATORY BODIES, GOVERNMENT AGENCIES, AND OTHER ORGANIZATIONS
- 5.7.3 KEY REGULATIONS: AI IN TOURISM
- 5.7.3.1 North America
- 5.7.3.1.1 SCR 17: Artificial Intelligence Bill
- 5.7.3.1.2 S1103: Artificial Intelligence Automated Decision Bill
- 5.7.3.1.3 National Artificial Intelligence Initiative Act (NAIIA)
- 5.7.3.1.4 The Artificial Intelligence and Data Act (AIDA)
- 5.7.3.2 Europe
- 5.7.3.2.1 The European Union (EU) - Artificial Intelligence Act (AIA)
- 5.7.3.2.2 General Data Protection Regulation
- 5.7.3.3 Asia Pacific
- 5.7.3.3.1 Interim Administrative Measures for Generative Artificial Intelligence Services
- 5.7.3.3.2 The National AI Strategy
- 5.7.3.3.3 The Hiroshima AI Process Comprehensive Policy Framework
- 5.7.3.4 Middle East & Africa
- 5.7.3.4.1 The National Strategy for Artificial Intelligence
- 5.7.3.4.2 The National Artificial Intelligence Strategy
- 5.7.3.4.3 The AI Ethics Principles and Guidelines
- 5.7.3.5 Latin America
- 5.7.3.5.1 The Santiago Declaration
- 5.7.3.5.2 The Brazilian Artificial Intelligence Strategy (EBIA)
- 5.8 PRICING ANALYSIS
- 5.8.1 AVERAGE SELLING PRICE TREND AMONG KEY PLAYERS, BY SOLUTION
- 5.8.2 INDICATIVE PRICING ANALYSIS, BY OFFERING
- 5.9 TECHNOLOGY ANALYSIS
- 5.9.1 KEY TECHNOLOGIES
- 5.9.1.1 Conversational AI
- 5.9.1.2 Autonomous AI & autonomous agent
- 5.9.1.3 AutoML
- 5.9.1.4 Causal AI
- 5.9.1.5 MLOps
- 5.9.2 COMPLEMENTARY TECHNOLOGIES
- 5.9.2.1 Blockchain
- 5.9.2.2 Edge computing
- 5.9.2.3 Sensors and robotics
- 5.9.2.4 Cybersecurity
- 5.9.3 ADJACENT TECHNOLOGIES
- 5.9.3.1 Big Data
- 5.9.3.2 IoT
- 5.9.3.3 Augmented Reality (AR)/Virtual Reality (VR)
- 5.10 PATENT ANALYSIS
- 5.10.1 LIST OF MAJOR PATENTS
- 5.11 PORTER'S FIVE FORCES ANALYSIS
- 5.11.1 THREAT OF NEW ENTRANTS
- 5.11.2 THREAT OF SUBSTITUTES
- 5.11.3 BARGAINING POWER OF BUYERS
- 5.11.4 BARGAINING POWER OF SUPPLIERS
- 5.11.5 INTENSITY OF COMPETITIVE RIVALRY
- 5.12 TRENDS/DISRUPTIONS IMPACTING CUSTOMER BUSINESS
- 5.13 KEY STAKEHOLDERS AND BUYING CRITERIA
- 5.13.1 KEY STAKEHOLDERS IN BUYING PROCESS
- 5.14 KEY CONFERENCES AND EVENTS, 2025
- 5.15 TECHNOLOGY ROADMAP FOR AI IN TOURISM MARKET
- 5.15.1 SHORT-TERM ROADMAP (2024-2025)
- 5.15.2 MID-TERM ROADMAP (2026-2028)
- 5.15.3 LONG-TERM ROADMAP (2029-2030)
- 5.16 BEST PRACTICES IN AI IN TOURISM MARKET
- 5.16.1 PERSONALIZATION AND CUSTOMER-CENTRIC APPROACH
- 5.16.2 SEAMLESS AI INTEGRATION WITH EXISTING SYSTEMS
- 5.16.3 REAL-TIME DATA UTILIZATION
- 5.16.4 ENHANCING OPERATIONAL EFFICIENCY
- 5.16.5 DATA PRIVACY AND SECURITY COMPLIANCE
- 5.16.6 AI FOR SUSTAINABILITY
- 5.16.7 CONTINUOUS LEARNING AND IMPROVEMENT
- 5.16.8 HUMAN-AI COLLABORATION
- 5.16.9 TRANSPARENCY AND TRUST
- 5.16.10 MONITORING AND MAINTENANCE
- 5.17 CURRENT AND EMERGING BUSINESS MODELS
- 5.17.1 SUBSCRIPTION SERVICES
- 5.17.2 DYNAMIC PRICING
- 5.17.3 SERVICE FEES
- 5.17.4 DATA MONETIZATION
- 5.17.5 AI-ENHANCED LOYALTY PROGRAMS
- 5.17.6 CUSTOMIZED TRAVEL PACKAGES
- 5.17.7 ANCILLARY REVENUE STREAMS
- 5.17.8 AI-POWERED TRAVEL ANALYTICS
- 5.18 AI IN TOURISM MARKET: TOOLS, FRAMEWORKS, AND TECHNIQUES
- 5.19 TRADE ANALYSIS (8542)
- 5.19.1 EXPORT SCENARIO OF PROCESSORS AND CONTROLLERS
- 5.19.2 IMPORT SCENARIO OF PROCESSORS AND CONTROLLERS
- 5.20 INVESTMENT AND FUNDING SCENARIO
- 5.21 IMPACT OF ARTIFICIAL INTELLIGENCE (AI)/GENERATIVE AI ON TOURISM
- 5.21.1 IMPACT OF AI/GENERATIVE AI ON TOURISM
- 5.21.2 USE CASES OF GENERATIVE AI IN TOURISM
6 AI IN TOURISM MARKET, BY OFFERING
- 6.1 INTRODUCTION
- 6.1.1 OFFERING: AI IN TOURISM DRIVERS
- 6.2 SOLUTIONS
- 6.2.1 TRAVEL
- 6.2.1.1 Booking management system
- 6.2.1.1.1 AI-powered automated booking to drive market growth
- 6.2.1.2 Virtual assistants & chatbots
- 6.2.1.2.1 AI-driven chatbots tailor suggestions to traveler preferences, enhancing satisfaction and market growth
- 6.2.1.3 Pricing & revenue management
- 6.2.1.3.1 AI-based solutions rapidly adapt to market shifts and demand changes, driving market growth
- 6.2.1.4 Customer experience management
- 6.2.1.4.1 AI automates inquiries and processes, enabling staff to focus on complex needs and enhance service quality, driving growth
- 6.2.1.5 Security & surveillance systems
- 6.2.1.5.1 AI helps in early threat detection and improves passenger experience, driving growth
- 6.2.1.6 Other travel solutions
- 6.2.2 HOSPITALITY
- 6.2.2.1 Booking management system
- 6.2.2.1.1 AI-driven systems streamline reservation process, reducing manual errors and increasing efficiency, driving growth
- 6.2.2.2 Virtual assistant & chatbots
- 6.2.2.2.1 Chatbots collect real-time guest feedback, delivering insights that enhance services and drive market growth
- 6.2.2.3 Pricing & revenue management
- 6.2.2.3.1 Automating pricing decisions and optimizing revenue enhances profit margins, driving market
- 6.2.2.4 Customer experience management
- 6.2.2.4.1 Automated sentiment analysis enhances guest satisfaction, driving market
- 6.2.2.5 Security & surveillance system
- 6.2.2.5.1 Improved facial recognition and behavior analysis by leveraging AI to drive market growth
- 6.2.2.6 Operational efficiency and resource management
- 6.2.2.6.1 AI-driven systems predicting equipment failures and maintenance needs driving market growth
- 6.2.2.7 Other hospitality solutions
- 6.3 SERVICES
- 6.3.1 PROFESSIONAL SERVICES
- 6.3.1.1 Personalized training programs and seamless integration of AI solutions in existing infrastructure to drive market growth
- 6.3.1.2 Consulting
- 6.3.1.3 System integration & implementation
- 6.3.1.4 Support & maintenance
- 6.3.2 MANAGED SERVICES
- 6.3.2.1 Outsourcing AI management that reduces system failures and disruptions through experienced providers to drive market growth
7 AI IN TOURISM MARKET, BY TYPE
- 7.1 INTRODUCTION
- 7.1.1 TYPE: AI IN TOURISM DRIVERS
- 7.2 OTHER AI
- 7.2.1 TECHNOLOGIES SUCH AS ML AND NLP IMPROVE SERVICES BY IDENTIFYING CUSTOMER BEHAVIOR TRENDS TO DRIVE MARKET
- 7.2.2 MACHINE LEARNING
- 7.2.3 NATURAL LANGUAGE PROCESSING
- 7.2.4 PREDICTIVE ANALYTICS
- 7.2.5 COMPUTER VISION
- 7.3 GENERATIVE AI
- 7.3.1 AI-BASED VIRTUAL TOURS AND GENERATION OF PERSONALIZED CONTENT AND RECOMMENDATION TO DRIVE MARKET
8 AI IN TOURISM MARKET, BY END USER
- 8.1 INTRODUCTION
- 8.1.1 END USER: AI IN TOURISM DRIVERS
- 8.2 TRAVEL INDUSTRY
- 8.2.1 AVIATION
- 8.2.1.1 AI optimizes operations and reduces delays
- 8.2.2 CAR RENTAL AND MOBILITY PROVIDERS
- 8.2.2.1 AI-powered chatbots and virtual assistants to drive growth
- 8.2.3 MARITIME TRAVEL
- 8.2.3.1 AI algorithms save time and fuel by analyzing weather and traffic patterns to recommend optimal routes
- 8.2.4 OTHER END USERS
- 8.3 HOSPITALITY INDUSTRY
- 8.3.1 HOTELS
- 8.3.1.1 AI analyzes occupancy patterns to optimize staff scheduling, reducing costs and driving market growth
- 8.3.2 RESORTS & THEME PARKS
- 8.3.2.1 AI apps offer real-time navigation, helping guests find attractions and services efficiently, driving market growth
- 8.3.3 CRUISE LINE OPERATORS
- 8.3.3.1 AI optimizes resource use, supporting sustainability and driving market growth
- 8.3.4 OTHER END USERS
9 AI IN TOURISM MARKET, BY REGION
- 9.1 INTRODUCTION
- 9.2 NORTH AMERICA
- 9.2.1 NORTH AMERICA: MACROECONOMIC OUTLOOK
- 9.2.2 US
- 9.2.2.1 Increased AI adoption in hospitality sector to drive market growth
- 9.2.3 CANADA
- 9.2.3.1 Government investments in AI technologies to boost market growth
- 9.3 EUROPE
- 9.3.1 EUROPE: MACROECONOMIC OUTLOOK
- 9.3.2 UK
- 9.3.2.1 Strong focus on improving customer experiences and passenger safety to drive market growth
- 9.3.3 GERMANY
- 9.3.3.1 Strong focus on Industry 4.0 and smart manufacturing to drive market growth
- 9.3.4 FRANCE
- 9.3.4.1 Increasing adoption of AI in aviation and investments by major players to drive growth
- 9.3.5 ITALY
- 9.3.5.1 Public investments and collaboration between private players to drive market growth
- 9.3.6 SPAIN
- 9.3.6.1 Rising integration of AI in popular tourist spots and AI-powered virtual guides to drive market growth
- 9.3.7 NORDIC COUNTRIES
- 9.3.7.1 Increasing demand for AI in aviation and maritime sector to drive market growth
- 9.3.8 REST OF EUROPE
- 9.4 ASIA PACIFIC
- 9.4.1 ASIA PACIFIC: MACROECONOMIC OUTLOOK
- 9.4.2 CHINA
- 9.4.2.1 Rising security demands and surge in tourism to drive market growth
- 9.4.3 JAPAN
- 9.4.3.1 Japan leveraging AI to enhance visitor experiences to drive sustainable market growth
- 9.4.4 INDIA
- 9.4.4.1 Growing demand for smart infrastructure for enhancing travel experience to drive market growth
- 9.4.5 AUSTRALIA & NEW ZEALAND
- 9.4.5.1 Enhanced customer experience at airports through AI-based solution to drive growth
- 9.4.6 SOUTH KOREA
- 9.4.6.1 AI-based translation services to drive market growth
- 9.4.7 ASEAN
- 9.4.7.1 Government initiatives for increasing tourism to drive AI in tourism market growth
- 9.4.8 REST OF ASIA PACIFIC
- 9.5 MIDDLE EAST & AFRICA
- 9.5.1 MIDDLE EAST & AFRICA: MACROECONOMIC OUTLOOK
- 9.5.2 KSA
- 9.5.2.1 Need for digital transformation under Vision 2030 to propel AI in tourism market
- 9.5.3 UAE
- 9.5.3.1 Investments in AI and medical tourism to drive market growth
- 9.5.4 KUWAIT
- 9.5.4.1 Tourism city initiative to boost AI in tourism market growth
- 9.5.5 QATAR
- 9.5.5.1 Government-driven digitalization to drive growth
- 9.5.6 SOUTH AFRICA
- 9.5.6.1 Increasing AI adoption to transform customer experiences in airports to drive market
- 9.5.7 REST OF MIDDLE EAST & AFRICA
- 9.6 LATIN AMERICA
- 9.6.1 LATIN AMERICA: MACROECONOMIC OUTLOOK
- 9.6.2 BRAZIL
- 9.6.2.1 Digital transformation in Brazilian tourism sector to drive market growth
- 9.6.3 MEXICO
- 9.6.3.1 Investments by major players and increasing utilization of AI-based solutions in hospitality sector to drive market
- 9.6.4 ARGENTINA
- 9.6.4.1 Growing digital economy and increasing tech-savvy population contributing to the adoption
- 9.6.5 REST OF LATIN AMERICA
10 COMPETITIVE LANDSCAPE
- 10.1 INTRODUCTION
- 10.2 KEY PLAYER STRATEGIES/RIGHT TO WIN
- 10.3 MARKET SHARE ANALYSIS
- 10.3.1 MARKET RANKING ANALYSIS
- 10.4 REVENUE ANALYSIS
- 10.5 COMPANY EVALUATION MATRIX: KEY PLAYERS, 2024
- 10.5.1 STARS
- 10.5.2 EMERGING LEADERS
- 10.5.3 PERVASIVE PLAYERS
- 10.5.4 PARTICIPANTS
- 10.5.5 COMPANY FOOTPRINT: KEY PLAYERS, 2024
- 10.5.5.1 Offering footprint
- 10.5.5.2 End user footprint
- 10.5.5.3 Region footprint
- 10.6 COMPANY EVALUATION MATRIX: STARTUPS/SMES, 2024
- 10.6.1 PROGRESSIVE COMPANIES
- 10.6.2 RESPONSIVE COMPANIES
- 10.6.3 DYNAMIC COMPANIES
- 10.6.4 STARTING BLOCKS
- 10.6.5 COMPETITIVE BENCHMARKING: STARTUPS/SMES, 2024
- 10.6.5.1 Detailed list of key startups/SMEs
- 10.6.5.2 Competitive benchmarking of key startups/SMEs
- 10.7 COMPETITIVE SCENARIO AND TRENDS
- 10.7.1 PRODUCT LAUNCHES
- 10.7.2 DEALS
- 10.8 BRAND/PRODUCT COMPARISON
- 10.9 COMPANY VALUATION AND FINANCIAL METRICS OF KEY AI IN TOURISM SOLUTION PROVIDERS
11 COMPANY PROFILES
- 11.1 KEY PLAYERS
- 11.1.1 SNOWFLAKE INC.
- 11.1.1.1 Business overview
- 11.1.1.2 Products/Solutions/Services offered
- 11.1.1.3 Recent developments
- 11.1.1.3.1 Product launches and enhancements
- 11.1.1.3.2 Deals
- 11.1.1.4 MnM View
- 11.1.1.4.1 Key strengths
- 11.1.1.4.2 Strategic choices
- 11.1.1.4.3 Weaknesses and competitive threats
- 11.1.2 SALESFORCE, INC.
- 11.1.2.1 Business overview
- 11.1.2.2 Products/Solutions/Services offered
- 11.1.2.3 Recent developments
- 11.1.2.4 MnM View
- 11.1.2.4.1 Key strengths
- 11.1.2.4.2 Strategic choices
- 11.1.2.4.3 Weaknesses and competitive threats
- 11.1.3 AMAZON WEB SERVICES, INC.
- 11.1.3.1 Business overview
- 11.1.3.2 Products/Solutions/Services offered
- 11.1.3.3 Recent developments
- 11.1.3.4 MnM View
- 11.1.3.4.1 Key strengths
- 11.1.3.4.2 Strategic choices
- 11.1.3.4.3 Weaknesses and competitive threats
- 11.1.4 IBM
- 11.1.4.1 Business overview
- 11.1.4.2 Products/Solutions/Services offered
- 11.1.4.3 Recent developments
- 11.1.4.4 MnM View
- 11.1.4.4.1 Key strengths
- 11.1.4.4.2 Strategic choices
- 11.1.4.4.3 Weaknesses and competitive threats
- 11.1.5 MICROSOFT CORPORATION, INC.
- 11.1.5.1 Business overview
- 11.1.5.2 Products/Solutions/Services offered
- 11.1.5.3 Recent developments
- 11.1.5.4 MnM View
- 11.1.5.4.1 Key strengths
- 11.1.5.4.2 Strategic choices
- 11.1.5.4.3 Weaknesses and competitive threats
- 11.1.6 NVIDIA CORPORATION
- 11.1.6.1 Business overview
- 11.1.6.2 Products/Solutions/Services offered
- 11.1.6.3 Recent developments
- 11.1.7 SAS INSTITUTE
- 11.1.7.1 Business overview
- 11.1.7.2 Products/Solutions/Services offered
- 11.1.7.3 Recent developments
- 11.1.8 SABRE CORPORATION
- 11.1.8.1 Business overview
- 11.1.8.2 Products/Solutions/Services offered
- 11.1.8.3 Recent developments
- 11.1.8.3.1 Product launches and enhancements
- 11.1.9 HUAWEI
- 11.1.9.1 Business overview
- 11.1.9.2 Products/Solutions/Services offered
- 11.1.9.3 Recent developments
- 11.1.10 [24]7.AI
- 11.1.11 VIRTUSA CORPORATION
- 11.1.12 APPIER INC.
- 11.1.13 TRAVELPORT WORLDWIDE LTD
- 11.1.14 AMADEUS IT GROUP, S.A.
- 11.1.15 ZENDESK
- 11.2 STARTUPS/SMES
- 11.2.1 DEVOX SOFTWARE
- 11.2.2 ALTEXSOFT
- 11.2.3 JIO HAPTIK TECHNOLOGIES LIMITED
- 11.2.4 SHR GROUP
- 11.2.5 DUVE
- 11.2.6 NEXSCIENT
- 11.2.7 PERSADO
- 11.2.8 CANARY TECHNOLOGIES
- 11.2.9 MIZE
- 11.2.10 FLYR
- 11.2.11 GEOVEA
- 11.2.12 LAYLA AI
12 ADJACENT/RELATED MARKETS
- 12.1 INTRODUCTION
- 12.2 CONVERSATIONAL AI MARKET
- 12.2.1 MARKET OVERVIEW
- 12.2.2 CONVERSATIONAL AI MARKET, BY OFFERING
- 12.3 SERVICES
- 12.3.1 CONVERSATIONAL AI MARKET, BY BUSINESS FUNCTION
- 12.3.2 CONVERSATIONAL AI MARKET, BY INTEGRATION MODE
- 12.3.3 CONVERSATIONAL AI MARKET, BY VERTICAL
- 12.4 CUSTOMER EXPERIENCE MANAGEMENT MARKET
- 12.4.1 MARKET DEFINITION
- 12.4.2 MARKET OVERVIEW
- 12.4.3 CUSTOMER EXPERIENCE MANAGEMENT MARKET, BY OFFERING
- 12.4.4 CUSTOMER EXPERIENCE MANAGEMENT MARKET, BY DEPLOYMENT TYPE
- 12.4.5 CUSTOMER EXPERIENCE MANAGEMENT MARKET, BY ORGANIZATION SIZE
- 12.4.6 CUSTOMER EXPERIENCE MANAGEMENT MARKET, BY VERTICAL
13 APPENDIX
- 13.1 DISCUSSION GUIDE
- 13.2 KNOWLEDGESTORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
- 13.3 CUSTOMIZATION OPTIONS
- 13.4 RELATED REPORTS
- 13.5 AUTHOR DETAILS
