In the UAE, this trend is even more pronounced. Data shows that 44% of hotel gross booking value and 37% of air bookings are made through online channels (Dubai Roads and Transport Authority), often via a smartphone while the traveller is already on the move.
This in-trip decision-making is where generative AI is delivering its most measurable impact. According to the TGM UAE Travel Insights 2025, Emirati and international travellers are increasingly acting as their own travel agents, prioritising flexibility and self-planned itineraries over rigid, pre-packaged tours.
AI tools are facilitating this by moving beyond simple search queries to providing real-time, context-rich recommendations.
Whether it is an itinerary adjustment based on weather conditions or a last-minute car rental booking via a marketplace app, the decision point has moved from a weeks-in-advance desktop session to a palm-of-the-hand interaction.
Algorithmic orchestration in the rental marketplace
Perhaps the most data-rich environment for machine learning where travel and mobility are concerned is the car rental sector.
The UAE’s car rental market, valued at US$1.15bn in 2023, is projected to climb to US$1.8bn by 2032. Such growth is underpinned by a highly-competitive supply base, with almost 4,000 rental firms operating in Dubai alone.
For an AI-driven marketplace, this level of fragmentation is something of an opportunity. When diverse demand meets a growing, multi-layered supply – including a 73% surge in high-end rentals and a 50% increase in EV adoption (Government of Dubai) – the need for sophisticated matching algorithms becomes paramount.