AI Agents Aim to Transform Traveler Relationships

AI agents could help airlines and other travel companies maintain customer relationships across the fragmented travel journey, potentially turning service interactions into a source of loyalty and direct revenue. A recent Skift Research survey of nearly 7,000 travelers indicates more than 60% of those aware of AI already use it for trip planning, though bookings remain concentrated on channels where price and trust dominate.

For airlines, the challenge is connecting disparate customer touchpoints over time. Customer-facing AI agents already handle individual service tasks like answering questions and changing reservations. The emerging opportunity, according to the report created in collaboration with a Skift partner, is for these agents to retain context from one interaction to the next, creating a more persistent relationship.

Erik Zahnlecker, agent product manager at Sierra, said long-running AI agents are designed to stay with both the customer and the task over days or months. "This kind of continuity can connect planning, booking, service, loyalty, and the months between trips into a more persistent customer relationship," Zahnlecker said.

Building Continuity Across the Travel Journey

Zahnlecker describes the current travel discovery process as a series of isolated, one-way touchpoints. AI agents could transform these into ongoing conversations by remembering prior interactions and customer preferences. This continuity could reduce the need for travelers to repeat information and allow agents to proactively reach out when relevant signals emerge.

The experience could also move seamlessly across communication channels like chat, email, SMS, and voice. A traveler could pause a phone conversation and request to continue via text, with the agent maintaining the context of the discussion.

From Flight Disruption to the Next Best Action

Flight disruptions present a clear test case for these agents. Instead of waiting for passengers to contact a crowded call center, a long-running agent could act on a disruption signal and reach out first. The agent could then weigh each traveler's priorities against airline rules in real time to find the best available rebooking option.

The agent's role would not necessarily end once rebooking is complete. It could carry context into reimbursement processes for eligible claims or monitor seat inventory to re-engage a traveler later if a preferred seat becomes available. Handling a disruption as one continuous journey, rather than a series of disconnected interactions, could be key to retaining the customer.

The Revenue Opportunity Between Trips

The period between trips is often an underused part of the customer relationship, frequently relegated to generic marketing emails. Zahnlecker sees this as a natural use case for AI agents, which could respond to signals like a completed trip, a fare drop to a preferred destination, or an event matching a traveler's interests.

Separate Skift Research on destination loyalty shows the value of the post-trip window. It identifies the 30 days after a trip as particularly important, with 52% of surveyed travelers saying personalized recommendations for a future visit would be helpful.

More personalized interactions could surface dormant demand, leading to direct bookings, upgrades, or ancillary purchases. "The more personalized the interaction, the more likely someone is to engage and see the agent as a trusted concierge," Zahnlecker said.

Personalization Changes the Economics of the Offer

Agents could also personalize offers between booking and departure, deciding which ancillaries-like seat upgrades, baggage, or Wi-Fi-are most relevant to each traveler. Loyalty program data could provide further context for timing and tailoring these offers.

Zahnlecker said offers can be shaped by customer data and previous outcomes, targeting travelers differently for cabin upgrades or loyalty enrollment. Higher conversion rates, stronger ancillary sales, and more repeat business could all contribute to customer lifetime value, with even modest gains becoming significant at scale.

The report cites an adjacent example from a leading travel platform, which uses a Sierra agent to help members clarify plan benefits and explore alternatives. According to Sierra, this agent contributed to a 5% increase in plan retention while achieving a 4.7 customer satisfaction score.

Staying Relevant Without Becoming Noise

For persistent engagement to work, travelers must find it useful. Relevance depends on signals from customer systems and what is learned through conversation. An agent that remembers a traveler's preference for premium economy, for instance, could monitor inventory silently rather than asking the traveler again.

"Over time, those conversations can build a richer customer profile that the agent can act on," Zahnlecker said. A known preference combined with a signal like new seat availability could create what he called "a reasonable moment to reach out."

The same challenge is emerging across the travel sector. Hotel groups need to connect reservation management, loyalty, and pre-arrival offers. OTAs are applying agents to refunds and check-ins, while cruise lines have similar opportunities across booking and onboard revenue. As AI agents take on more of the customer journey, their ability to share context across service, loyalty, and commercial functions will be critical.