Agentic AI: Four Futures for Flight Booking by 2030s

AI Set to Transform Flight Booking Landscape

Agentic Artificial Intelligence (AI) holds the potential to fundamentally alter how individuals search for, compare, and ultimately book flights in the coming decade. However, the exact trajectory of this transformation remains uncertain, according to a recent scenario planning exercise conducted by TNMT, Lufthansa Innovation Hub's research arm.

Over the past few months, leading up to September 2026, TNMT undertook a structured process, evaluating 40 trends spanning technology, regulation, consumer behaviour, geopolitics, and airline distribution. This assessment aimed to identify trends with the highest impact and uncertainty, informing a framework for understanding future market dynamics in the 2030s.

Two Critical Uncertainties Define Future Scenarios

TNMT's analysis revealed two critical uncertainties that will shape the future of flight booking. The first is 'Trust in Agentic Booking', which assesses how comfortable travellers will become with delegating search, comparison, decision-making, and transaction processes to AI agents.

The second, 'Context Ownership', explores who will control the essential customer data – including preferences, travel history, loyalty information, and payment credentials – that enables an AI agent to make informed choices.

These two axes combine to create four distinct future scenarios for flight booking in the 2030s, providing a framework to understand potential market shifts rather than predicting a single outcome.

The 'Grounded Ambitions' Scenario: Intermediaries Gain Control

One detailed scenario, termed 'Grounded Ambitions', outlines a future where AI-assisted travel search becomes commonplace, yet consumers decline to hand over the final booking decision to autonomous agents. In this 2030s outlook, airlines have not adapted their commercial infrastructure rapidly enough.

Their digital systems, such as airline.com and mobile applications, remain focused on conventional direct channels. Fares, seat maps, ancillary services, and loyalty benefits are only partially accessible in a format that AI agents can reliably use. This gap means intermediaries become crucial, bridging AI-powered discovery with human-controlled booking processes.

Consequently, indirect sales begin to surpass direct bookings, forcing airlines to absorb the increasing cost of serving AI-generated searches without securing a proportionate share of the resulting transactions.

Airlines Absorb Costs, Loyalty Programs Struggle

In the 'Grounded Ambitions' scenario, intermediaries provide more structured and machine-readable data, a gap that, if it persists, disadvantages airlines. For instance, a traveller in 2031, needing a flight, might use an AI assistant that accesses their calendar, travel history, and preferences.

The assistant quickly presents itinerary options based on price, schedule, and journey time. However, it struggles to confirm preferred seats, lounge eligibility, upgrade options, baggage benefits, or loyalty points, as this information remains siloed within airline systems.

This requires the traveller to ask follow-up questions, triggering numerous additional searches across airline and intermediary platforms. The AI assistant ultimately ranks options based on the information it can confidently evaluate, leading the traveller to book via an Online Travel Agent (OTA) and then separately contact the airline to verify loyalty benefits.

This process means loyalty programs, designed to influence booking decisions and drive direct engagement, fail to activate effectively.

Implications for Airlines: Rising Costs, Diminished Engagement

The 'Grounded Ambitions' future presents significant commercial challenges for airlines. They continue to pay for making schedules and fares accessible to a rapidly growing volume of AI-generated searches, with OTAs playing a central role in this distribution.

However, as travellers do not complete bookings directly through AI agents or airline channels, direct customer interactions decline. Look-to-book ratios surge, driving up infrastructure costs without a corresponding increase in direct revenue or customer ownership.

The scenario demonstrates that by the time an airline enters the booking process, the most commercially valuable moments – influencing the decision – have already occurred elsewhere. This shift compels airline leaders to consider who should bear the cost of infrastructure serving AI-generated search volumes if travellers do not permit agents to complete bookings on their behalf.

Airlines must therefore prioritise making their full offer, including loyalty benefits, transparent and machine-readable for AI agents, or risk further disintermediation.