AI in Personalised Travel: The Future of Smart Tourism in 2026

📅 Published: January 14, 2026
🔄 Last Updated: October 27, 2026

Analysis India: AI in personalised travel is changing how people discover destinations, plan itineraries, select accommodation and experience new places. Travel companies are moving beyond conventional search filters towards intelligent systems that understand traveller preferences, budgets, interests and real-time conditions. These developments are creating new opportunities for airlines, hotels, online travel agencies and destination management organisations.

The transformation is particularly important in India, where domestic tourism, digital travel services and regional destination development are expanding rapidly. Artificial intelligence can help travellers find experiences that match their interests while enabling tourism businesses to improve customer service, manage demand and promote destinations beyond established tourist centres.

According to Grand View Research, the India AI in tourism market generated revenue of USD 145.1 million in 2025 and is projected to reach USD 839.3 million by 2033. The research firm estimates a compound annual growth rate of 23.46 percent between 2026 and 2033. These estimates indicate a growing commercial opportunity for AI-powered travel services in India.

At the same time, the Ministry of Tourism is strengthening the country’s digital tourism ecosystem through initiatives involving artificial intelligence, digital promotion and destination management. The opportunity now extends beyond recommending hotels or attractions. AI in personalised travel could help connect the entire journey, from initial inspiration and itinerary planning to local experiences, travel assistance and post-trip engagement.

Understanding the broader technology landscape is equally important, and our detailed analysis of AI market trends and industry adoption in 2026 explains how artificial intelligence is transforming business models across multiple industries.

How AI Is Changing Personalised Travel and Smart Tourism

Traditional travel planning requires visitors to compare destinations, transport options, accommodation, weather conditions and activities across multiple websites. The process can become complicated when travellers have different budgets, accessibility requirements, dietary preferences or interests. Artificial intelligence can simplify these decisions by analysing information and presenting options that better match an individual’s requirements.

An AI-powered travel assistant can use natural language to understand requests such as a three-day family holiday, a heritage-focused weekend, a budget pilgrimage or a nature trip with limited driving. It can then suggest destinations, estimate journey times, organise activities and recommend suitable accommodation. More advanced systems can revise itineraries when weather conditions, flight schedules or opening hours change.

This development is helping tourism businesses move from generic recommendations towards contextual services. A family travelling with children may receive suggestions for shorter journeys and family-friendly attractions. A business traveller may prefer convenient transport, flexible accommodation and restaurants close to meeting locations. A traveller interested in culture may receive recommendations for museums, traditional food, local crafts and guided heritage walks.

The value of AI in personalised travel depends on the accuracy of the underlying information. A recommendation is useful only when prices, opening hours, availability, transport connections and local conditions are sufficiently reliable. Travel companies therefore need to combine AI models with verified supplier information, current booking systems and appropriate human support.

Global AI in Tourism Market Size and Growth Forecast

The commercial potential of artificial intelligence in tourism is expanding as travel companies invest in recommendation engines, automated customer support, intelligent search and predictive analytics. According to Grand View Research, the global AI in tourism market was valued at approximately USD 3.37 billion in 2024 and was estimated at USD 4.26 billion in 2025. Its published forecast projects the market to reach approximately USD 13.87 billion by 2030.

The forecast represents substantial growth in the market for AI technologies used in tourism. However, this market should not be confused with total global travel revenue. It covers a narrower technology market involving AI solutions and related services rather than all spending on flights, hotels, restaurants and tourism activities.

Global AI in Tourism Market Forecast

Year	Market value in USD billion	Data status
2024	3.37	Historical estimate
2025	4.26	Estimated market value
2030	13.87	Forecast

Source: Grand View Research AI in Tourism Market Analysis.

The market’s expansion is supported by several business applications. Recommendation systems help travel platforms match products with customer preferences. Generative AI makes it easier to search for trips through conversational questions. Predictive models support demand forecasting and revenue management, while automated assistants can answer routine questions before, during and after a journey.

These applications also create opportunities for smaller travel operators. Independent hotels, local tour companies and destination management organisations can use third-party AI services without developing their own large technology platforms. The main challenge is ensuring that these tools use dependable information and integrate effectively with existing booking and customer service systems.

The growth of AI-powered travel services is closely connected to changes in traveller behaviour and destination demand, which are also important themes in our travel and tourism market analysis.

India AI in Tourism Market Outlook Through 2033

India is becoming an important market for intelligent travel services because of its large domestic tourism base, growing digital economy and varied destination landscape. Travellers visit the country for religious tourism, heritage, wildlife, beaches, medical treatment, business, adventure and regional cultural experiences. Each segment presents different opportunities for personalisation.

Grand View Research’s India market outlook estimates that the AI in tourism market generated USD 145.1 million in revenue in 2025. The same forecast projects revenue of USD 839.3 million by 2033, representing a compound annual growth rate of 23.46 percent from 2026 to 2033.

India AI in Tourism Market Forecast

Indicator	Value
Market revenue in 2025	USD 145.1 million
Forecast market revenue in 2033	USD 839.3 million
Forecast CAGR, 2026 to 2033	23.46 percent
Largest offering segment in 2025	Solutions
Share of solutions in 2025	83.46 percent

Source: Grand View Research India AI in Tourism Market Outlook. The figures are market research estimates and forecasts. The forecast does not represent the size of India’s entire tourism industry.

The solutions segment accounted for 83.46 percent of the Indian AI in tourism market in 2025, according to the same research. This suggests that technology products, platforms and software applications represented the largest offering category in the report’s market segmentation. Services are identified as the fastest-growing offering segment, indicating opportunities for implementation, integration, customisation and ongoing support.

India’s market opportunity extends beyond large online travel agencies. Hotels can use AI to improve guest communication and recommend services. Tour operators can create itineraries for different customer groups. Local tourism businesses can make regional experiences easier to discover, while destination authorities can use data to understand visitor movement and improve planning.

Nevertheless, market growth will depend on more than the availability of AI tools. Data quality, digital skills, affordability, multilingual performance and integration with booking infrastructure will influence adoption. Smaller operators may also require training and technical assistance before they can use these systems effectively.

Similar data-driven approaches are being adopted beyond tourism, as explained in our analysis of AI-powered forecasting tools helping Indian retailers plan inventory, where predictive models support demand planning and operational decisions.

India’s Tourism Growth Creates a Larger Opportunity for Personalisation

The scale of Indian tourism provides an important foundation for AI-enabled services. The Ministry of Tourism’s official dashboard reports 4,286.90 million domestic tourist visits in 2025, up 45.6 percent from 2024. It also reports 25.27 million foreign tourist visits, an increase of 21.36 percent.

The same dashboard records 20.22 million international tourist arrivals in 2025, including 9.15 million foreign tourist arrivals and 11.07 million non-resident Indian arrivals. These indicators measure different aspects of tourism and should not be treated as interchangeable. In particular, tourist visits count visits to destinations, while arrivals measure entry or arrival events under the relevant statistical definitions.

India’s Tourism Performance in 2025

Tourism indicator	2025 value	Change from 2024
Domestic tourist visits	4,286.90 million	Up 45.6 percent
Foreign tourist visits	25.27 million	Up 21.36 percent
International tourist arrivals	20.22 million	Down 1.71 percent
Foreign tourist arrivals	9.15 million	Down 8.07 percent
Non-resident Indian arrivals	11.07 million	Up 4.26 percent
Indian national departures	32.83 million	Up 6.3 percent

Source: Ministry of Tourism India Tourism Data Dashboard, 2025 data. Figures are reproduced from the dashboard; the reporting definitions differ between visits and arrivals.

These figures show why tourism personalisation matters for India. The volume of domestic travel creates opportunities for destination discovery, regional itinerary planning, transport coordination and accommodation recommendations. International visitors, meanwhile, may need multilingual information, assistance with local transport, cultural guidance and reliable access to tourism services.

The scale of domestic visits also highlights the need for careful interpretation. A visit is not necessarily a unique individual traveller. One person can make multiple visits during a reporting period. Therefore, domestic tourist visits should not be interpreted as the number of individual Indians who travelled.

For tourism businesses, the commercial opportunity lies in converting a large and diverse travel market into more relevant experiences. AI can help visitors compare destinations, discover activities suited to their interests and organise travel around available time and budget. For destination authorities, the same technologies can support visitor information, demand monitoring and the promotion of less crowded locations.

Government Initiatives Are Strengthening India’s Digital Tourism Ecosystem

India’s digital tourism strategy is creating a broader foundation for technology-enabled travel services. The Ministry of Tourism signed a memorandum of understanding with Google India in June 2026 to strengthen digital promotion of Indian destinations through digital technologies, artificial intelligence, data-driven insights and capacity building.

Speaking about the collaboration, Union Minister for Tourism and Culture Gajendra Singh Shekhawat said, “Digital technologies have the potential to create immersive experiences that can showcase the glory and grandeur of India’s cultural sites to audiences across the world. By harnessing cutting-edge digital technologies, we can transform the way travellers discover, experience and engage with India’s rich cultural and natural heritage.”

The partnership is intended to strengthen the digital visibility of Indian destinations and improve the use of travel trends, traveller behaviour and digital engagement insights in tourism promotion. It also includes capacity-building activities for Ministry officials in digital marketing, campaign optimisation, content creation and emerging technologies, including AI.

The government subsequently announced the National Digital Tourism Stack on World Tourism Day 2026. The initiative is designed to improve the discoverability, accessibility and trustworthiness of India’s tourism offerings through shared digital infrastructure. The government has described capabilities such as verified provider information, search and discovery, payments, ratings and grievance redressal.

The Ministry also announced the National Mission for Alternative Destinations under Dekho Apna Desh Campaign 2.0. Its objective is to promote lesser-known destinations as alternatives or complements to heavily visited locations. This approach could help AI travel systems offer more varied recommendations instead of repeatedly directing visitors towards the same established attractions.

The National Digital Tourism Stack is being developed with the Open Network for Digital Commerce and support from the International Centre for DPI Innovation and Advancement. The government has outlined phased implementation, with a pilot planned for January 2027. It should therefore be described as an initiative under development rather than a fully operational nationwide booking system.

These developments are relevant to AI in personalised travel because useful recommendations depend on the quality and availability of destination information. Better digital records of tourism providers, experiences and visitor services can help technology platforms present more complete information. However, the practical benefits will depend on implementation, data coverage, interoperability and participation by tourism businesses.

How AI Creates Personalised Travel Experiences

Intelligent Itinerary Planning

AI can help travellers organise a trip around their interests, available time, spending limits and preferred pace. Instead of selecting every activity separately, a traveller can describe the type of experience they want and receive a suggested itinerary. The system can consider journey times, attraction opening hours, weather and the geographic distance between locations.

For Indian travellers, this could be useful for a short pilgrimage, a family holiday, a heritage circuit or a weekend trip from a major city. A visitor planning a trip to Varanasi, for example, might want to combine cultural sites, local food, an early morning river experience and suitable transport. An AI assistant can organise these preferences into a practical plan, provided the underlying information is current and verified.

Personalisation should not mean that every suggested itinerary is accepted without review. Travellers need to confirm prices, operating hours, transport arrangements and reservation requirements before making payments. AI can make planning easier, but it cannot guarantee that every recommendation will be available or appropriate.

Personalised Hotel and Accommodation Recommendations

Accommodation selection depends on more than price. Travellers may prioritise location, accessibility, family facilities, breakfast, business amenities, sustainability or proximity to attractions. AI recommendation engines can analyse these preferences and rank available options according to the traveller’s stated requirements.

Hotels can also use customer preferences to improve the guest experience. Subject to appropriate consent and data protection practices, systems may help staff prepare relevant arrival information, answer common questions, recommend local activities and respond to service requests. Such applications are most effective when AI supports hotel employees rather than replacing human assistance for complex situations.

For smaller Indian accommodation providers, third-party software can provide some of these capabilities without the expense of developing proprietary technology. However, the usefulness of the service will depend on accurate property details, updated availability and the quality of the booking integration.

Real-Time Travel Assistance

Travel plans can change because of weather, traffic, cancellations, delayed flights or unexpected closures. AI-powered travel assistants can combine available operational information with a traveller’s itinerary to suggest alternative arrangements. For example, an outdoor activity could be moved to a clearer day, or an alternative transport option could be presented after a disruption.

The connected-trip approach is particularly relevant here. Glenn Fogel, CEO of Booking Holdings, discussed the role of AI and personalisation in reducing friction across travel in a February 2026 interview with McKinsey. He explained, “The idea of the connected trip is to use technology personalization to make sure we are giving customers what they want and doing it in a way that provides the most value.”

The underlying business opportunity is to coordinate separate parts of a journey. A traveller may need a flight, an airport transfer, hotel accommodation and activities at the destination. Better connections between these services can make it easier to manage changes and reduce the time spent contacting multiple providers.

Multilingual Travel Information and Local Discovery

Language remains an important consideration in a country as diverse as India. AI-based translation and conversational systems can help travellers access destination information, understand basic instructions and discover local experiences. These capabilities can be valuable for international visitors as well as domestic travellers exploring regions where they are unfamiliar with the local language.

Multilingual systems can also help local guides, homestays and small tourism businesses reach a wider audience. A traveller may be more likely to explore a lesser-known cultural attraction when reliable information is available in a familiar language.

However, machine translation can misinterpret local names, cultural context, safety instructions or nuanced historical information. Tourism operators should review important content, particularly information concerning religious customs, restricted areas, transport rules and visitor safety.

What Industry Leaders Are Saying About AI in Travel

Statements from industry leaders indicate that the next stage of travel technology will involve more than automated recommendations. Companies are working towards experiences that connect discovery, planning, booking and support, while recognising that trust remains essential.

Xavi Amatriain, Chief AI and Data Officer at Expedia Group, said in the company’s April 2026 AI Trust Gap announcement, “Travelers don’t have a technology problem with AI. They have a trust problem.”

Expedia Group’s survey of more than 5,700 adults across the United States, United Kingdom and India found that 53 percent were comfortable letting AI suggest travel options, 42 percent used or would use AI to monitor prices, and 40 percent used AI to help build itineraries. The company also reported that 68 percent preferred booking with a trusted travel brand over an AI chatbot or agent, even when AI booking was available.

These are findings from a company-commissioned YouGov survey, not a census of all global travellers. The distinction matters because the results describe the survey sample and should not automatically be generalised to every country or traveller group.

The findings nevertheless highlight a practical challenge. Travellers may welcome AI for inspiration and planning while expecting established booking providers to remain responsible for payments, cancellations, refunds and customer service. This makes transparency, accurate information and clear accountability important elements of successful personalisation.

Ariane Gorin, CEO of Expedia Group, also described the company’s direction in May 2026: “As we celebrate 30 years, we’re focused on advancing our intelligent, trusted global marketplace that takes on the complexity of travel, so travelers and partners can focus on what really matters: unforgettable experiences.”

Taken together, these statements suggest that AI adoption in tourism will depend on a combination of convenience, dependable supplier information and trusted customer support. Travel businesses that integrate these elements are better positioned to turn experimentation with AI into sustained customer use.

AI in Personalised Travel and Sustainable Tourism

Smart tourism also involves managing the impact of visitors on destinations. Popular attractions can experience congestion, pressure on local infrastructure, seasonal demand peaks and environmental stress. AI and data analytics can help destination managers understand visitor flows, estimate demand and communicate alternative travel options.

For example, a destination management system could use available visitor counts and booking patterns to identify periods of heavy demand. Travel platforms could then recommend different visiting hours or nearby attractions, where reliable data and local capacity information are available. Such systems could help distribute tourism spending across more locations and support local businesses.

India’s National Mission for Alternative Destinations is relevant to this objective because it seeks to promote lesser-known destinations and distribute tourism demand more widely. AI-powered discovery tools could support the initiative by making alternative locations easier to find and by helping travellers plan realistic itineraries.

Nevertheless, technology alone cannot make tourism sustainable. Destination authorities still need to consider waste management, transport capacity, water availability, conservation rules and community priorities. Recommendations should reflect local carrying capacity and avoid directing excessive visitor numbers towards fragile sites.

AI in personalised travel can contribute to more responsible tourism when it helps visitors make informed choices and supports destinations in managing demand. Its effectiveness will depend on whether the technology is connected to practical policies and reliable local information.

To understand the wider technological developments behind intelligent travel assistants, recommendation engines and automated services, explore comprehensive guide to AI and technology trends in 2026.

Business Opportunities for Indian Travel Companies

The growth of AI-powered travel services creates opportunities across the tourism value chain. Online travel agencies can use conversational search and recommendation systems to simplify trip discovery. Airlines can improve customer communication and offer more relevant ancillary services. Hotels can use predictive systems to support revenue management and guest service, while tour operators can produce itineraries tailored to specific customer segments.

Regional tourism businesses may benefit from better digital discovery. A homestay, local guide or specialist tour provider can attract travellers who are interested in rural experiences, regional cuisine, cultural activities or nature-based tourism. Better structured information and integration with digital distribution channels can make these businesses easier to discover and compare.

Technology suppliers also have opportunities to provide booking integration, multilingual assistants, analytics, demand forecasting and customer support automation. For smaller businesses, subscription-based services and shared platforms may be more practical than building an AI system from the ground up.

The main commercial challenge is demonstrating measurable value. Tourism businesses should assess whether AI improves booking conversion, reduces response times, increases customer satisfaction, lowers service costs or supports repeat visits. They should also track errors, complaints and the cost of maintaining accurate data.

A well-designed AI system should solve a clear customer or operational problem. Adopting a chatbot simply because competitors are using one may produce limited benefits if the underlying booking information and service processes remain fragmented.

Challenges and Risks of AI-Powered Personalisation

Personalisation requires information about traveller preferences, searches, bookings and interactions. This creates privacy responsibilities for travel businesses. Organisations should collect only information needed for a defined purpose, explain how it will be used and provide appropriate controls for consent, access and deletion under applicable laws.

Accuracy is another concern. AI-generated travel recommendations may include incorrect prices, unavailable accommodation, outdated attraction information or impractical connections. Travel businesses should connect systems to verified data sources, make important limitations clear and provide a route to human support.

Bias can also affect recommendations. If an AI system relies heavily on historical bookings or popular destinations, it may repeatedly promote established attractions while overlooking smaller operators and less familiar locations. Better data coverage and deliberate inclusion of regional providers can help reduce this problem.

There is also a risk of excessive automation. Travellers may require human assistance when dealing with cancellations, medical needs, accessibility problems, lost documents or safety incidents. AI should support the resolution process rather than become a barrier to reaching a responsible person.

For Indian tourism businesses, the strongest approach is likely to combine AI efficiency with human judgement, accurate local knowledge and transparent customer service. The objective should be a more useful travel experience, not automation for its own sake.

Future Outlook for AI in Personalised Travel

The next phase of tourism technology is likely to focus on systems that can coordinate multiple parts of a journey. Travellers may increasingly describe their requirements in ordinary language and receive suggested itineraries that combine transport, accommodation, activities and local experiences. With appropriate permissions and reliable integrations, some systems may also help monitor bookings and suggest changes when circumstances shift.

India has several conditions that could support this development, including a large domestic travel market, diverse regional destinations and ongoing investment in digital tourism infrastructure. Government initiatives to improve destination discovery and provider information may help make more tourism services accessible through digital channels.

However, the future size of the market should be understood through published forecasts rather than treated as a guaranteed outcome. Adoption will depend on the quality of digital infrastructure, consumer trust, supplier participation and the ability of businesses to demonstrate a return on investment.

AI in personalised travel is therefore best understood as an enabling layer across the tourism industry. It can help travellers make better-informed choices, help businesses serve customers more efficiently and help destination managers understand demand. Its long-term success will depend on delivering accurate, transparent and genuinely useful experiences.

Conclusion

AI in personalised travel is moving tourism towards more responsive planning, relevant recommendations and connected customer services. Global market forecasts point to expanding investment in AI technologies for tourism, while India’s own market outlook suggests significant potential through 2033. The country’s domestic tourism scale and digital tourism initiatives provide a strong context for further adoption.

Industry leaders are also emphasising that customer trust remains central to the future of AI-enabled travel. Travellers may welcome intelligent planning tools, but they still need reliable booking processes, clear accountability and support when something goes wrong.

For Indian travel companies, the opportunity is to combine technology with dependable information and local expertise. Businesses that use AI to improve real customer outcomes, while protecting privacy and maintaining human support, can contribute to a more personalised, accessible and sustainable tourism ecosystem.

Frequently Asked Questions

Sources and further reading

Grand View Research. India AI in Tourism Market Outlook.

Ministry of Tourism, Government of India. India Tourism Data Dashboard.

Press Information Bureau. Ministry of Tourism and Google India digital tourism partnership, June 2026.

Press Information Bureau. National Digital Tourism Stack and tourism initiatives announced in September 2026.

Expedia Group. AI Trust Gap research, April 2026.

McKinsey. Interview with Glenn Fogel, CEO of Booking Holdings, February 2026.