How Will We Travel in 2045? Ten Bets for the AI Era
At a glance
- Travellers currently spend hours researching trips across hundreds of pages; AI will absorb this burden to optimise outcomes with minimal effort.
- AI will manage travel disruptions—rebooking, refunds, ground transport, real-time alternatives—removing stress management work, though travel itself remains inherently stressful.
- AI-driven pricing will move beyond averages to dynamic, demand-aware models using conversational signals (budget, flexibility, loyalty) for true personalisation.
- Data quality emerges as the decisive competitive factor; reliable data enables AI agents to reason safely, personalise effectively, and build traveller trust.
- Incumbents with scale, datasets, global reach, and operational depth are best positioned to deploy AI industry-wide; startups will innovate but lack deployment advantage.
What the report covers
OAG's CEO Filip Filipov presents ten strategic predictions for the travel industry by 2045, framed around how AI will reshape core traveller behaviours and industry dynamics. The analysis spans aviation, accommodation, mobility, and ancillary services, examining how AI will address persistent challenges—complexity, stress, fragmentation, over-tourism, and infrastructure constraints. Published February 2026, it serves industry stakeholders including DMOs, hoteliers, and travel-tech operators navigating the AI era.
Key findings
Travel research currently imposes significant cognitive burden on travellers, who spend hours comparing flights, hotels, and extras across hundreds of pages per trip. The report predicts AI will absorb this research workload, allowing travellers to optimise outcomes—price, timing, experience—without expending effort. This shift reflects the underlying assumption that travellers are 'lazy' and will increasingly delegate repetitive, comparative tasks to agentic systems.
Operational stress will persist in travel due to growing demand, constrained infrastructure, weather, and disruptions. However, the nature of traveller burden will change fundamentally. Agentic AI will handle disruption management tasks: anticipating issues, rebooking flights, processing refunds, coordinating ground transport, and proposing real-time alternatives. The report argues AI removes the work of managing stressors, not the stressors themselves.
Price sensitivity and comparison shopping are structural traveller behaviours that won't disappear. The report forecasts AI will handle search and filtering behind the scenes, including access to private and loyalty-based offers. Conversational AI will capture deep intent signals—budget, flexibility, loyalty status, preferences—enabling dynamic, demand-aware pricing beyond current averages. This requires scalable technology and high-quality data foundations.
Travellers will retain decision authority over bookings despite advanced automation, as travel choices carry emotional, personal, and financial stakes. The report positions the future division of labour as: AI executes work; humans retain approval authority. This reflects a bet that traveller autonomy and control remain non-negotiable, even as AI capabilities mature.
Travel supply fragmentation across airlines, hotels, mobility, and services will persist structurally. Rather than consolidation, the report predicts AI will unify the experience by assembling itineraries, detecting constraints, optimising combinations, and managing disruptions across providers as a single coherent workflow. Success depends on high-quality operational data, which the report identifies as decisive for building trust in AI-driven services.
Key numbers
| Metric | Value |
|---|---|
| Hours spent by travellers researching trips | Several hours per trip |
| Pages visited per trip during research | Hundreds of pages |
Figures as published in the source; forecasts and survey results are labelled as such in the note.
Why it matters
DMOs & destinations
AI agents will redirect demand away from over-tourism hotspots toward under-visited alternatives using real-time visibility into supply, congestion, and pricing. DMOs must ensure high-quality destination data, competitive positioning, and infrastructure information to attract AI-directed travellers. This represents a fundamental shift in demand distribution mechanisms away from traditional marketing channels.
Hotels & hospitality
Hoteliers will face AI-driven dynamic pricing and demand redistribution, requiring superior data infrastructure and operational transparency. The report emphasises data quality as decisive for building traveller trust in AI-mediated bookings. Hotels must prioritise real-time availability, rate, and experience data accuracy to compete in AI-brokered distribution and access conversational intent signals for personalisation.
Travel tech & distribution
Scale, data, integration, and distribution will determine competitive advantage over invention. Incumbents with massive datasets, operational depth, and brand trust gain compounding advantages as AI becomes a commodity layer. Travel-tech players must prioritise data quality and unified supply integration; startups can innovate, but incumbents are positioned to deploy AI at industry scale.
Methodology and limits
This brief is based on the publicly available summary and blog post only. The full report ('Travel 2045: A 20-Year Outlook for the AI Era') is referenced but not provided in the source text. The analysis presents ten strategic 'bets'—expert predictions from OAG's CEO—rather than survey data, experimental results, or quantitative modelling. No sample size, confidence intervals, or methodological details are disclosed. The predictions are forward-looking estimates for 2045 based on observed travel industry trends and AI capability trajectories.
Official source
The report is © OAG. This brief is an original editorial summary by TourismIntel — it quotes only figures published in the source and never reproduces the document.
Check the official statistics on Pulse
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