AI in Airlines: Passenger Experience Tutorial (2026)

Sunday 22:15 - the delay wave NPS will flatten

Berk is airline CX Analytics lead. After a weather night:

• Post-flight NPS softens; verbatims blame “no update,” “gate change chaos,” and “baggage last”
• App one-stars spike on check-in and rebooking flows
• Airport social outruns the care queue
• Leadership wants a journey map and stage scores - not one blended detractor number

Tuesday’s pack will say NPS −3. It will not tell Berk whether the root cause is disruption comms, digital rebooking UX, or baggage reclaim handoffs.

Same discipline we used on air cargo applies to passengers: map → score → AI root cause → owners.

What is AI in airlines? (CX definition)

AI in airlines in a CX context means using AI to read, classify, and explain passenger feedback at scale - NPS, tickets, app reviews, social during disruption - then route insights to airport ops, cabin, digital, and care owners.

Two disciplines first (same as cargo):

1. Journey mapping - book → check-in → security/gate → onboard → baggage → disruption recovery
2. Scoring - friction by stage, not one blended NPS

Tutorial: Berk’s 6-step airline AI playbook

Step 1 — Inventory passenger voice channels Post-flight NPS, app/web, airport social, care tickets, lounge feedback. Disruption voice often lives outside the survey.

Step 2 — Map the passenger journey Name stages and handoffs. If “delay” and “baggage” share one bucket, owners stay unclear.

Step 3 — Score friction by stage Volume, urgency, and emotion by stage - so this week’s trust burn is visible.

Step 4 — Unify VoC with stage tags Same “no update” complaint in app, Twitter, and care gets one theme ID + one journey stage.

Step 5 — Run AI themes + RCA with segments Cabin, route, hub, frequent flyer tier. A short-haul gate mess is not the same root cause as long-haul baggage.

Step 6 — Assign owners and measure weekly Airport ops, digital product, care, baggage. Theme volume + stage score + time-to-fix.

Same scenario: Turkish Airlines Terminal × Pivony

We use the same reference as the aviation operations tutorial:

Pivony was selected as one of 17 startups in the Turkish Airlines Terminal Acceleration Program (powered by Turkish Cargo). In the Turkish Cargo PoC, Pivony worked on customer journey mapping and scoring and analysing customer voice at scale - the same operating system airline CX teams need for passenger journeys: map stages, score friction, then act.

Terminal Acceleration Program news → Demo Day / Turkish Cargo milestone →

What to look for in airline AI / VoC

1. Explicit passenger journey map
2. Stage scores under disruption, not only headline NPS
3. App + airport social + care in one stream
4. AI RCA with route / cabin segments
5. Named owners and weekly close-the-loop

Related Pivony resources

• Aviation sibling tutorial (cargo focus)
• Terminal Acceleration Program
• Turkish Airlines / Cargo milestone
• CJPM guide · Free RCA scan

Next step

Run Berk’s playbook on last week’s post-flight verbatims: free RCA scan or book a demo with your passenger journey stages.

Related: How AI automates RCA in VoC