// Airline Agent Experience
Scans pass.
Agents fail.
AI agents are starting to browse, compare and book for real customers. Last Mile sends a real browser agent through real airline journeys and checks the only thing that matters: did the task actually complete?
// Benchmark — 7 airlines tested
Who completes the task
| # | Airline | Completed / measurable | Access-gated | Top failing signal |
|---|---|---|---|---|
| 1 | Riyadh Air | 0 / 15 | 1 | Failure transparency |
| 2 | easyJet | 0 / 2 | — | Discoverability |
| 3 | Emirates | 0 / 2 | 1 | Input affordances |
| 4 | Lufthansa | 0 / 2 | 1 | Input affordances |
| 5 | airBaltic | 0 / 1 | — | Task completion |
| 6 | Delta | 0 / 1 | 1 | Task completion |
| 7 | Qatar Airways | 0 / 1 | — | Input affordances |
Ordered by measurable-run coverage, not pass rate — every airline in this sample passed zero measurable runs. Riyadh Air accounts for 15 of the 24 measurable runs; the other 6 carriers contribute one or two tasks each. 2 additional runs failed on infrastructure grounds and are correctly excluded, not counted as fails.
Scope of this sweep
Methodological information
0 of 24 passed
16 distinct tasks across 7 airlines
4 of 28 runs
airlines in this sweep
A spot-check, not an industry sweep — concentrated on one carrier. This is 7 airlines, 16 distinct tasks — Qatar Airways, Lufthansa, Riyadh Air, airBaltic, easyJet, Emirates, Delta. A mix of agent models drove — claude-sonnet-4-6 (15), kimi-k2.5:cloud (10), unattributed (6), run 2026-07 to 2026-08.
Top failure signals across the measurable sample: failureTransparency (11) · inputAffordances (5) · discoverability (4) · taskCompletion (4)
Access-gated is not failure
Access-gated is not failure. A booking-reference lookup that correctly asks for a booking reference is a site working as designed. 4 of 28 airline runs hit an honest access wall — a login, PNR, or payment gate the agent hit as expected. Gated runs are excluded from the Index — never counted as a pass, never counted against the site.
// The loop
Assess. Diagnose. Optimize.
Key takeaways
Takeaway_01
Zero of 7 airlines completed a measurable task.
Takeaway_02
Failure transparency is the top failure signal — 11 of 24 measurable runs went dark instead of erroring legibly.
Takeaway_03
The controlled site we own goes from 0% to 100% — hostile to ready, same tasks, same check.
// WebMCP case study
Judge WebMCP by the outcome it produces
Friction Airways is a controlled airline site we own, published in three WebMCP-readiness profiles. Same site, same 21-task measurable slice — only the profile changes.
Hostile's fails cluster on one signal: 18 of 21 measurable fails returned no machine-readable answer at all; ready has zero measurable fails. This is the evaluate → diagnose → optimize → retest loop in miniature, run on one controlled site, not an airline-industry claim.