Abstract: As the national “artificial intelligence +” strategy continues to advance, the cultural tourism industry is standing at a key node from information digitization to process intelligent adaptation. AI large models are no longer just marketing gimmicks or content generation tools, but have begun to enter the deep waters of planning, services, operations, governance and business transformation.
The report believes that during the "15th Five-Year Plan" period, vertical large models will become the core variable for the intelligent upgrading of the cultural tourism industry. A dedicated model system built around industry knowledge, real-time data, business closed-loop and trusted governance will reshape the competitive boundaries of destinations, scenic spots, OTAs, content platforms and cultural tourism technology companies.
Introduction: From "digitalization" to "intelligent adaptation", the cultural tourism industry has entered a new era driven by AI
In the past ten years or so, the digitalization of cultural tourism has mainly focused on online booking, electronic ticketing, smart scenic spots and data dashboards. The core is to move offline resources online and make management processes visible. The emergence of AI large models has further enabled the cultural and tourism system to understand needs, generate content, plan paths, schedule resources and assist decision-making.
For tourists, smart services are moving from "searching for answers" to "generating solutions"; for scenic spots and destinations, operating systems are moving from "post-facto statistics" to "real-time perception and dynamic response"; for governments and industry platforms, cultural tourism governance is also shifting from single-point system construction to data, models, and scenario collaboration.
The growth in market size confirms this change. Smart tourism is no longer a single information project, but a comprehensive industry covering data base, intelligent interaction, content production, spatial computing, robot terminals and operation services.
Division and integration: Why are vertical large models the key to success in the cultural tourism industry?
General-purpose large models have powerful language understanding, content generation and reasoning capabilities, but they still encounter obvious boundaries in cultural tourism scenarios: destination information is updated frequently, and ticketing, weather, passenger flow, activities and transportation are highly real-time; history and culture, local knowledge, tour logic and service specifications require in-depth industry Know-How support. In the absence of trusted data and business constraints, the model is prone to hallucinations and it is difficult to directly enter the service closed loop.
The value of vertical large models lies in combining industry knowledge base, real-time data, RAG search enhancement, scenario rules and business processes to make model answers more accurate, actions more controllable, and results trackable. In the cultural tourism scene, it must understand not only content, but also resources, operations, and safety boundaries.
The key to the future is not to choose between a general model and a vertical model, but to "combine general and specialized models": using a general model to provide basic understanding and generation capabilities, using cultural and tourism-specific knowledge, data and tool chains to complement accuracy, timeliness and business execution capabilities, and ultimately forming an intelligent system that is implementable, operable, and sustainably optimized.
New battlefield panorama: AI+ cultural tourism application scenarios, core players and industry chain map
For C-side tourists, AI is covering the complete journey before, during and after the trip. Before the tour, the focus is on inspiration discovery, itinerary planning and product matching; during the tour, it emphasizes intelligent tour guides, real-time Q&A, route adjustment and multi-language services; after the tour, it focuses on content generation, social sharing, repurchase recommendations and membership operations.
For B-side and G-side, the value of AI is more towards operational efficiency and governance capabilities, including passenger flow prediction, marketing placement, digital human explanation, content asset production, scenic spot safety inspection, complaint work order diversion, destination public opinion monitoring and cultural tourism resource scheduling. AI is not only the front-end service entrance, but also reshaping the back-end operation system.
Industrial players are rapidly gathering. Products such as Ctrip's "Daodao" and TripGenie, Tongcheng's "Chengxin AI" and DeepTrip, Fliggy's "Wenyiwen" and Mafengwo's "AI Xiaoma" have strengthened the entrance to travel services; Global DigiTech Innovation Co., Ltd., a new generation of end-to-end smart cultural tourism model system, builds industry capabilities from knowledge, models, agents to closed-loop business for destinations, scenic spots and industrial operations.
In the broader industry chain, AI digital human tour guides, virtual and real integration experiences, drones and digital twin inspections, smart terminals and robot services are working together with large models to form a new generation of cultural tourism infrastructure. Whoever can connect model capabilities, scenario resources, and delivery and operation capabilities will be more likely to establish barriers in the new battlefield.
Research and Judgment of New Opportunities: Capital Flow and Business Model Evolution
Capital is shifting from purely conceptual AI applications to scenario-based companies that can generate industry data, dedicated models, verifiable effects and sustained income. Opportunities for the cultural tourism industry lie not only in application interfaces, but also in the combined capabilities of data governance, model services, content assets, operating systems and smart terminals.
Business models are also evolving simultaneously. The traditional project system still exists, but more compound interest models are emerging: SaaS subscriptions for scenic spots and destinations, RaaS results-as-a-service based on marketing, passenger flow and operating results billing, and regional cultural tourism digital operations promoted by "platform + capital", all may become growth paths for cultural tourism AI companies.
At the same time, intelligent hardware and spatial computing push AI services from the screen to the real space. Exoskeleton robots, inspection robots, drones, XR equipment and IoT sensing networks will open more application portals for cultural tourism services, scenic spot safety, outdoor experience and assistance for special groups.
Conclusion: Grasp the pulse of AI transformation and jointly create a new future for the cultural tourism industry
When AI large models enter the cultural tourism industry, what really changes is not a single tool, but the way the industry is organized: content, services, operations, governance and business transformation will be put into the same intelligent closed loop for continuous iteration.
Facing the "15th Five-Year Plan", the cultural tourism industry needs to seize two "promotions" and one "improvement": promote the in-depth integration of models and scenarios, promote the collaborative opening of data and business processes, and improve industry service quality, operational efficiency and governance capabilities.
AI does not replace the humanistic experience in cultural tourism, but allows high-quality content, precise services and efficient operations to better reach tourists and industry sites.
For companies with industry understanding, technology accumulation and delivery capabilities, this round of change is not only a technological upgrade, but also a historical opportunity to redefine the value chain of the cultural tourism industry.