The global travel industry has embraced artificial intelligence to streamline operations, personalise customer experiences, and optimise pricing. Airlines such as Singapore Airlines and Emirates use AI for dynamic pricing and predictive maintenance, while hotel groups like Marriott International and Accor deploy chatbots and biometric check-ins. Online travel agencies including Booking Holdings and Expedia Group rely on generative AI to tailor recommendations. Yet a growing body of evidence suggests the infrastructure powering these advances—massive data centres—is placing unsustainable pressure on water, energy, and land resources, particularly in regions that are also key tourism destinations.
On 3 June 2025, the United Nations University published a report titled Environmental Cost of Artificial Intelligence: Carbon, Water, and Land Footprints, which quantifies the hidden costs of AI. The report's abstract states: “AI is not only a digital technology, but also a material system with measurable environmental costs. (Our) central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land… The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, land use, mineral extraction, and e-waste can be concentrated in specific communities and regions.”
Water Scarcity and Competition with Local Communities
The British Council notes that data centres require billions of litres of water annually to cool high-powered processors. This is especially problematic in arid regions where tech giants build server farms. In places like Arizona, Spain, and parts of Southeast Asia, data centres compete directly with local communities and resorts for freshwater. The United Nations declared in January 2025 that the world has entered an “era of water bankruptcy,” with global water systems irrevocably damaged. Experts estimate that AI-related water consumption could equal the annual domestic needs of 1.3 billion people by 2030. For hotels in water-stressed destinations—such as those in the Maldives, Bali, or the Middle East—this could mean severe rationing, making it impossible to maintain swimming pools, golf courses, or basic guest sanitation.
The energy demands of AI data centres also complicate the travel industry's decarbonisation efforts. Airlines like Delta Air Lines and Lufthansa Group, cruise lines such as Carnival Corporation and Royal Caribbean Group, and hotel chains including IHG Hotels & Resorts have all set net-zero targets that depend on access to clean electricity. Yet the rapid expansion of AI infrastructure is driving up demand for power, making it harder and more expensive for travel companies to secure renewable energy. The global land footprint for AI data centres is expected to exceed 14,500 square kilometres by the end of the decade, encroaching on natural landscapes and wildlife habitats that are often the very attractions drawing tourists.
Despite these challenges, AI has delivered undeniable benefits to travel. Operational efficiency gains have been significant: airlines use AI for asset management and finance tasks, improving productivity while cutting costs. Personalisation engines analyse travel history and online behaviour to offer bespoke recommendations, as seen with OTAs like Kayak and Skyscanner. Chatbots and virtual assistants provide 24/7 support, handling bookings and cancellations without human staff. Dynamic pricing tools help carriers like Ryanair and hotel groups like Hilton maximise revenue. And AI optimises flight routes and biometric security systems, speeding up airport processes.
However, the industry must now confront the trade-offs. The UNU report underscores that the environmental costs of AI are not evenly distributed: the benefits flow globally, but the burdens—water withdrawals, land use, mineral extraction, and e-waste—fall on specific regions. For travel professionals, this raises urgent questions. Should a resort in a water-scarce region continue to invest in AI-driven guest experiences if the data centre supporting it exacerbates local water shortages? Can airlines justify AI-powered route optimisation if the energy required undermines their carbon reduction pledges?
Some companies are already taking steps. Radisson Hotel Group, for instance, is expanding its Southeast Asia Pacific pipeline with new openings while exploring energy-efficient data centre partnerships. The International Hospitality Management (IIHM) has launched a Global AI Hospitality Education Council with over 60 nations to promote sustainable AI practices. Meanwhile, ATPCO's Architect Pricing Platform, now used by 32 airlines globally, demonstrates how AI can be deployed with a focus on efficiency rather than resource intensity.
As the travel sector reevaluates its AI expansion, the path forward will require collaboration between technology vendors, energy providers, and tourism stakeholders. Data centre operators must prioritise locations with access to renewable energy and water-efficient cooling systems. Travel companies should demand transparency from their AI suppliers about the environmental footprint of the models they use. And industry associations, such as the World Travel & Tourism Council, can advocate for policies that align AI growth with sustainability goals.
The stakes are high. If left unchecked, the very technology that has boosted travel metrics could degrade the destinations that sustain the industry. As the UNU report makes clear, the environmental cost of AI is not a distant concern—it is already reshaping the resource landscape. For travel professionals, the time to act is now.
