At the 2026 TravelDaily Conference in Beijing, Li Shaohua, co-founder and CEO of Beijing Shilv Network Technology and former president of Alibaba's Fliggy, delivered a keynote that reframed the conversation around artificial intelligence in travel. His central thesis: travel AI has entered the competition for execution.
Li argued that while large language models excel at understanding user intent and AI agents can organize tasks, the actual fulfillment of travel services still depends on traditional travel companies. AI is reshaping the service process, but it has yet to take over transactions and payments. The gap between planning and booking, he suggested, is where the next wave of opportunity lies.
Two real-world tests of ChatGPT-5.6
To illustrate his point, Li shared two personal experiments conducted during a summer trip to the United States, where he used only ChatGPT-5.6 without any third-party tools.
The first was a family excursion from New York to the Washington, D.C. area, including visits to the White House and Capitol Hill. The AI generated an itinerary broken down to five-minute intervals and proactively advised against renting a car, recommending train travel instead. Li followed the plan almost exactly. The only friction points were purchasing train tickets and attraction tickets, which required manual clicks to external links because the AI could not place orders or process payments on his behalf.
The second test was a 15-day inbound trip to China, starting in New York and covering nine destinations including Shenzhen, Guangzhou, Guilin, Chengdu, and Shanghai. This coincided with the beta testing of an inbound travel product being developed internally by Shilv Technology. Li, who has two decades of industry experience, said he could hardly find fault with the AI-generated itinerary. More notably, the AI flagged several easily overlooked risks: tight train ticket availability during China's National Day holiday, boat ticket arrangements in Yangshuo, and the connection between Chengdu and Shanghai.
These tests led Li to a direct conclusion: GPT has already rewritten the personal trip planning process. Travelers no longer need to search, compare, and repeatedly revise itineraries. Instead, they can delegate research, planning, and adjustments to AI through continuous conversation, simply by expressing their intent clearly.
The remaining gaps: booking, payment, and trust
Li acknowledged that booking and payment remain the main obstacles. However, he does not see them as insurmountable. He pointed to the airline industry as proof that AI can eventually move deeper into the transaction process, citing examples of AI-driven fare optimization and dynamic pricing already in use by carriers.
But the biggest gap, in Li's view, is not capability—it is trust. He cited research comparing the Chinese and U.S. markets. The U.S. travel market is approximately 35% to 40% larger than China's, which is the world's second-largest. One survey he referenced found that 61% of U.S. consumers already use agentic services, 83% of travel companies have adopted general-purpose AI capabilities, and 39% of consumers use AI for trip planning. Yet another survey showed that only 8% of consumers actually complete bookings directly through AI.
That disparity—between using AI for inspiration and entrusting it with a transaction—is the crux of the matter. Li believes the industry is at a tipping point. As AI agents become more reliable and integrated with booking systems, the trust gap will narrow. He called on travel companies to invest in AI-native infrastructure that can handle not just planning but also secure, seamless transactions.
Li's remarks echo broader trends in the sector. Recent data shows that AI adoption for trip planning has jumped 64% in six months, and platforms like Agoda are already testing AI trip planning assistants. Meanwhile, China's inbound tourism boom is testing service quality as international travelers increasingly rely on AI tools.
For travel professionals, the message is clear: AI is not a futuristic concept but a present-day competitive lever. Those who can bridge the gap between AI-driven planning and actual booking will define the next era of travel distribution.
