Agentic AI for airline carriers

Quiq’s AI agents proactively message passengers with rebooking options and new flight details before they call in, so the counter and phone lines don’t absorb the full brunt of a weather delay or mass cancellation. Because the agent reasons through multi-step requests instead of following a script, it can authenticate a passenger by PNR, pull real-time inventory, and confirm a new itinerary in one conversation. One national airline serving 40 million+ passengers a year cut average conversation time 16% after deploying Quiq, largely because its AI agent could resolve full IROP rebookings without escalating to a human. That airline’s customer story has more detail on how disruption handling changed after launch.

Yes. Quiq’s Verified Intelligence cross-references every compensation claim against the passenger’s PNR, delay length, and the relevant regulatory matrix (EU261, DOT, or an airline’s own policy) before a response goes out, so valid claims get resolved on the spot and edge cases get escalated to a human with the full record attached. That verification step matters in aviation more than most industries, since a wrong answer isn’t just a bad experience, it’s a compliance exposure. Every decision leaves a full audit trail, so compliance and legal teams can see exactly why a claim was approved, denied, or routed to a person, instead of trusting the AI’s judgment blind.

Quiq’s AI agents handle the requests that fill up phone queues and chat windows: adding a checked bag, changing a seat, checking baggage status, modifying a reservation, or redeeming loyalty points. Because the AI is grounded in the airline’s own reservation system rather than a fixed decision tree, it can complete the transaction directly instead of describing the steps and sending the passenger elsewhere. One airline that deployed Quiq now resolves more than 40% of complex requests, including reservation updates and flight changes, without a live agent, across voice, chat, and messaging. That shift freed its guest care team to focus on the judgment-heavy cases that still need a person. Read the full National Airline story.

When a passenger asks about a seat change, a status check, or a delay, that moment of attention is also a moment to offer something relevant, like a seat upgrade, lounge access, or extra loyalty points, completed with in-thread payment instead of a separate email or callback. Quiq’s AI agent recognizes these high-intent moments because it already has the full context of the conversation and the passenger’s record, so the offer fits what’s actually being asked about rather than feeling like an upsell bolted onto a support ticket. This turns routine service interactions, which most airlines treat as a pure cost center, into a source of incremental revenue.

The AI agent hands off with a complete conversation summary and the relevant account details already attached, so the passenger doesn’t have to re-explain what they need and the agent doesn’t spend the first few minutes of the call reconstructing the situation. This is part of why one airline saw a 20% reduction in conversation time specifically on escalated inquiries after moving to Quiq: agents started every handoff with full context instead of from scratch. The same Process Guides and knowledge base power the AI agent and the human-assist tools, so the guidance an agent sees lines up with what the AI already tried, instead of two disconnected systems giving conflicting answers.

Results vary by carrier and starting point, but one national airline saw a 40%+ automated resolution rate across voice, chat, and messaging, a 16% reduction in average conversation time, and a 20% reduction in conversation time on escalated inquiries after replacing a rigid, menu-driven chatbot and a stalled Voice AI pilot with a single agentic AI agent from Quiq. That airline now handles 7 million+ conversations a year through the AI agent on one platform instead of stitching together separate vendors for voice, chat, and messaging. The clearest ROI usually shows up in fewer live-agent minutes per resolved issue and one consolidated reporting view instead of several. See the full results in the National Airline case study.