AI and Smart Tourism in China 2026: Insights for Travel Brands, Hotels and Destinations

AI in tourism is moving from hype to infrastructure

China’s travel industry is entering a more practical AI phase. With the smart tourism market expected to exceed RMB 14.5 trillion in 2025, AI is not as a future-facing add-on, but as a real operating layer across the tourism value chain. The shift is being driven by three forces: stronger computing and model capabilities, a fast-growing AI ecosystem around platforms such as DeepSeek, and wider adoption across industries that is pushing tourism to digitise faster.

Data source: Endata Inc.

What that means in simple terms is this:

• the base layer is cloud, computing power and AI models

• the middle layer connects AI tools to business systems and workflows

• the front layer applies AI to travellers, travel businesses and destinations.

  
  

The most immediate use cases are already clear:

• conversation services for smart customer support and digital tour guides

• recommendation services for itineraries, hotels and travel products

• prediction services for passenger flow and price forecasting.

  
  

The market is also starting to split between what is working now and what is still emerging. Tourism information services, guided navigation and experience upgrades are among the most mature AI applications today, while AI trip-planning assistants are still at an earlier stage but showing strong demand. At the same time, AIGC marketing, digital humans, smart facilities and public-sector destination management are widening the role AI can play in tourism.

Travel planning is becoming AI’s first mainstream battleground

One of the clearest messages in the report is that AI travel planning is where consumer adoption is becoming most visible. More than 70% of respondents have already formed some level of AI travel-tool habit, with 27% saying they use such tools often and 45% saying they use them occasionally. Usage is especially strong in first-tier cities, where the “frequent use” rate reaches 31.44%, versus 27.67% in second-tier cities, 27.20% in third-tier cities and 23.78% in fourth-tier cities.

Data source: Endata Inc.

That habit is still concentrated in the pre-trip stage. 57% of AI tourism tool use happens before travel, versus 43% during the trip, while post-trip use is negligible. Within that pre-trip window, itinerary planning accounts for 46% of segmented AI use, followed by smart recommendations at 36%, inspiration at 10%, price monitoring at 5% and information assistance at 3%.

Data source: Endata Inc.

The tool mix also shows how fast the market is diversifying. The report identifies five main types of AI itinerary-planning tools: general large language models, OTA-embedded AI assistants, content-platform AI tools, third-party standalone apps and regional AI travel assistants built by destinations or local tourism departments. General models such as Doubao and DeepSeek are becoming especially common, which means travel planning is no longer controlled by one platform type. It is increasingly being contested across search, content, commerce and destination-owned ecosystems at the same time.

The strongest consumer use cases are practical, not futuristic

Data source: Endata Inc.

Travellers are not starting with the most futuristic AI applications. They are starting with the most practical ones. Translation tools are the most commonly used AI travel tool at 55.1%, followed by AI travel advisers at 48.9%, dynamic price prediction at 46.2% and visa assistants at 40.0%.

That tells us something important. AI adoption in travel is still being led by utility. Travellers may like the idea of AI-powered travel, but they are far more likely to use it when it reduces friction, cuts uncertainty and makes planning easier.

Across the wider “AI + tourism” landscape, that same pattern holds. Information services and experience enhancement are among the most mature applications, while itinerary planning is still developing despite strong demand. In short, traveller demand is moving fast, but product maturity is still catching up. That leaves a clear opening for travel brands that can build useful, dependable AI services before habits fully settle.

Hotels are showing what scaled AI deployment really looks like

On the enterprise side, hotels are the clearest proof point that AI in tourism is moving from pilot mode into operating reality. Hotels are the most widely adopted segment in tourism-enterprise AI usage in 2025 H2, accounting for 26.6% of industry distribution.

The main business scenarios are also becoming clearer. Leading hotel AI use cases include:

• intelligent customer service at 52.5% 

• marketing content and video generation at 41.0% 

• personalised recommendation at 41.0% 

• itinerary planning and development at 32.8% 

• demand forecasting at 29.7%.

  
  

The report makes that shift tangible. More than 80% of hotel groups have already incorporated AI and data into their medium- to long-term strategy, with customer service, marketing decision-making and operations management as the main landing areas.

On the service side, AI is being used for multilingual assistance, personalised guest recommendations and real-time service coordination. On the commercial side, it supports precision marketing, content generation, demand forecasting and strategic planning. On the operational side, it helps power customer-source analysis, pricing recommendations and revenue monitoring.

The wider message is clear: AI’s value in hospitality is no longer limited to guest-facing experience. It is increasingly showing up in margin management, labour efficiency and faster decision-making.

Destinations and scenic areas are earlier-stage, but strategically important

Data source: Endata Inc.

Destination-side adoption is still at an early stage, but arguably just as important. The report shows that scenic areas are still in the first phase of large-model deployment:

• 50.0% have not yet connected to large AI models

• 41.7% are preparing to connect 

• 8.3% are already connected

  
  

That may sound early, because it is. But it also means the market is still open. Scenic-area operators are not stepping into an overcrowded AI landscape yet; they are entering a formative one, where early adoption can still shape visitor experience, operational standards and destination differentiation.

The first meaningful use cases are already taking shape across three priority areas:

• Visitor services and experience 

  AI is being used where travellers feel it most directly. This includes integrated information support, intelligent guides, real-time recommendations, and more immersive formats such as AR and voice-led experiences.

  
  

• Scenic-area operations and management

  AI is becoming a management tool as much as a service tool. Scenic areas are starting to use it for smarter operations, scheduling, resource deployment and data-supported decision-making.

  
  

• Cultural protection and dissemination.

  The opportunity is broader and more strategic. Large models can help digitise cultural heritage content, improve interpretation and support wider dissemination, giving destinations a stronger way to turn cultural assets into richer visitor storytelling.

Conclusion: AI is becoming the operating layer of modern travel

The clearest takeaway is that AI in tourism is no longer one trend among many. It is becoming the connective layer between traveller intent, travel planning, service delivery and operating efficiency.

Consumers are already using AI heavily in the pre-trip stage. Hotels are already deploying it across service, marketing and revenue management. Destinations are still earlier in maturity, but the models for AI-driven guidance, storytelling and information services are quickly becoming more concrete.

The next question is no longer whether to “use AI”. It is where AI creates the clearest commercial advantage. Is it in smarter trip planning, faster customer response, better yield management, stronger destination discovery, or more immersive on-site experience? The brands that answer that question with operational focus, not just innovation theatre, will be the ones that move first as China’s smart tourism market scales into its next phase.

If your business is now looking to translate these shifts into a sharper travel, hospitality or destination strategy in China, get in touch with us.