ANZAirline (flag carrier)Launch · $50K
Air New Zealand

Built for the seasonal surge — agentic disruption service for Air New Zealand's tourism-driven network

Air New Zealand's demand is a tourism tide — southern-summer peaks, long-haul dependencies and weather that can strand a day's network — while engine-availability constraints have made every disruption harder to recover; an agentic frontline that rebooks proactively in the languages of its visitor markets absorbs the surges a fixed Auckland contact center cannot, at a cost a mid-sized carrier can defend.

Entry use case
Disruption rebooking and proactive passenger communication
Expected outcome
Absorb seasonal and weather-driven contact spikes with proactive multilingual rebooking, protecting the airline's famously high service reputation without surge staffing.
Recommended next step
Pre-summer planning session with customer care: scope a Launch pilot on disruption rebooking and Mandarin/Japanese service, live before the December peak.
What we understand

Air New Zealand's operating reality

Air New Zealand is the flag carrier hub-and-spoked on Auckland, heavily dependent on inbound tourism and long-haul connections to Asia and North America.

Public fact

The airline has faced prolonged fleet-availability pressure from industry-wide engine maintenance issues, publicly cited as constraining capacity and resilience.

Public fact

Air New Zealand has publicly announced work with OpenAI, one of the first airlines to do so — AI adoption is on-strategy, and vendor pluralism must be the pitch frame.

Public fact

Demand and disruption both peak in the southern summer, when weather events can cascade across the whole domestic-international connection bank.

Reasoned inference

Visitor-market passengers (China, Japan, Korea, US) need disruption help in their own languages, which a fixed NZ-based contact center cannot staff economically.

Reasoned inference

Repeat refund- and credit-status contacts likely form a long tail after each disruption wave.

Seller hypothesis — validate

Validate with the account team before outreach: Scope of the OpenAI collaboration and openness to multi-vendor AI · Disruption-day contact multipliers and current multilingual coverage · PSS integration constraints (Amadeus/other) for automated rebooking

Build vs buy

Why we have a right to win here

Partner-led target

Technically capable but needs industry workflows, integration, acceleration, or managed operations

Evidence: Air New Zealand is AI-forward for its size — the publicly announced OpenAI collaboration shows appetite and some internal capability — but a mid-sized flag carrier does not build voice platforms; it partners for applied AI, and the pitch frame is vendor pluralism: a benchmarkable Gemini frontline for disruption and multilingual service alongside existing AI commitments.

Why they won't build the full stack: A carrier of this scale cannot fund or staff a production conversational-AI platform on top of fleet-constraint firefighting; its AI collaborations are applied-use-case partnerships, not platform builds, and seasonal surge capacity in Mandarin, Japanese and Korean is precisely what a bought platform delivers faster than any internal roadmap.

What management is signalling

Air New Zealand has publicly cited prolonged engine-availability constraints (industry-wide maintenance issues) as limiting capacity and network resilience, alongside sustained inbound-tourism recovery in its visitor markets.

Reported factFY2025 results commentary and public disclosures · 2025

GTM implication: Fleet constraints make disruption more likely while tourism demand grows — sell elastic multilingual disruption care as brand protection precisely where operational risk is concentrated.

Cost-discipline programs likely continue while capacity constraints cap revenue upside, making surge staffing for seasonal peaks hard to justify.

Inferencerecent investor communications (validate) · 2025-2026

GTM implication: Frame the Launch pilot as surge-staffing cost avoided plus saved rebookings, measurable within one southern-summer season.

What already exists (don't pitch this)
  • Air NZ app with self-service booking management
  • Publicly announced OpenAI collaboration on applied AI use cases
  • Airpoints loyalty program
  • Disruption notification capability via app and SMS
What customers still can't do end-to-end (pitch this)
  • →Multilingual disruption service for visitor markets (Mandarin, Japanese, Korean) around the clock
  • →Transactional rebooking in-channel during network-wide events
  • →Refund/credit status self-service that suppresses the post-disruption repeat-contact tail
  • →Surge capacity beyond the fixed Auckland contact center
Opportunity map

Where agentic communications pays off first

WorkflowWhy it matters hereValueComplexitySpeedChannels
Disruption rebooking and proactive passenger communication
Proactive rebooking in the passenger's language; spike absorbed without surge staffing.
One weather event can strand international connections across the network; recovery speed is the brand.
Friction today: Disruption floods a fixed contact center; international visitors queue in a foreign language at their worst travel moment.
App chatSMSVoiceEmail
Multilingual visitor-market service desk
Native-quality service across visitor languages, around the clock, at software cost.
Tourism NZ demand from Asia is the growth engine; service in Mandarin, Japanese and Korean is a competitive differentiator against one-stop Gulf and Asian carriers.
Friction today: Non-English service depends on scarce specialist staff in limited time windows.
App chatVoice
Watch the change

Disruption rebooking and proactive passenger communication: today vs the agentic model

Scenario: Fog closes Auckland just as a Shanghai flight lands with 40 onward domestic connections; each affected visitor gets rebooking options in Mandarin in-app before reaching the transfer desk, and the crewed desk handles only the complex itineraries — the queue never forms.
Today
same interaction, two worlds
Agentic layer
Disruption call spike
10× volume, melted queues
suppressed by proactive rebooking
Assumption
Cost per contact
$13.50 median assisted
$1.84 median self-service
Benchmark
QA coverage
1–2% sampled
100% scored
Platform capability
Sources & assumptions
  • · Disruption call spike: Operator-reported pattern (assumption); suppression measured in pilot
  • · Cost per contact: Gartner customer service cost benchmarks, 2024
  • · QA coverage: Platform capability: every interaction logged and evaluated
  • · Gartner, customer service cost benchmarks (2024): $13.50 median assisted vs $1.84 self-service per contact
  • · McKinsey, digital-first collections research: 20–25% NPL reduction among leaders; up to 40% opex reduction with gen AI
  • · Baymard Institute: ~70% average cart abandonment (meta-analysis)
  • · IAMAI–Kantar via IBEF (2025): 900M+ Indian internet users; 98% consume Indic-language content
  • · LeadSquared and vendor funnel studies: 78% of students choose the first institution to respond (directional, vendor data)
  • · HDI / ITSM operator benchmarks: $15–25 per L1 ticket; 40–60% of L1 volume is resets/status (validate per customer)
  • · Conventional-flow wait times and volumes are typical operator patterns — assumptions to replace with the customer's own baseline
  • · Agentic-flow behaviors (context retention, 100% logging, in-line policy checks) are platform capabilities, not projections
Recommended solution

One integrated stack, opinionated for this account

Channels · Tilicho Labs
App chatSMSVoiceEmail

Voice & channel orchestration, telephony, conversational execution, session/state, routing, integration build. Capability coverage validated during implementation.

Intelligence · Google Cloud
Gemini reasoningEnterprise groundingWorkflow agentsMulti-agent orchestrationGoverned actionsEvaluation & analytics
Systems · Air New Zealand
PSS/reservationsDisruption managementPayments/refundsKnowledge baseLoyalty

API access to these systems is the critical-path dependency.

Trust & languages
EnglishMandarinJapaneseKorean

Identity-bound sessions, policy-bounded actions, 100% audit logging, human approvals at defined points, in-tenant intelligence.

Business case

The economics, with your numbers

Addressable monthly interactions500K
Seller assumption — replace in discovery
Current cost per interaction ($)$6.5
Industry benchmark scale — validate
Automation / assistance rate (%)55%
Seller assumption — pilot proves this
$3.3M
Current operating cost / mo
$20.3M
Modelled gross benefit / yr
0.0 mo
Payback on Launch
1731%
3-yr ROI (modelled)
Automated/assisted interactions per month275K
Modelled AI run-cost per month (usage + cloud, system estimate)$96K
New monthly operating cost$1.6M

All figures are modelling estimates from the labeled inputs above — nothing here is customer-provided yet. The pilot's first job is replacing these assumptions with Air New Zealand's measured baseline. Package price covers implementation only; recurring usage billed separately.

Recommended package

Launch — $50K implementation

Launch · $50K · A focused, fast production pilot8–10 weeks to a live, measured pilot

Why this package for Air New Zealand: A focused disruption-workflow pilot fits a mid-sized carrier's budget and its existing AI vendor commitments; success creates the expansion case into everyday service and loyalty.

Included
  • Up to 3 channels
  • One priority workflow
  • Limited enterprise integrations (1–2 systems)
  • API credential & security setup
  • Core conversational + workflow configuration
  • Basic analytics
  • Controlled production pilot with defined success criteria
Not included
  • ✕Usage & consumption (billed separately)
  • ✕Additional workflows
  • ✕Multi-geography rollout
  • ✕Managed operations
Recurring costs (separate from the package)

Packages cover implementation and integration only. Recurring costs are billed separately: Tilicho Labs platform usage (~$0.15/call-min indicative, usage only), Google Cloud consumption, telephony/carrier charges, managed operations, and support & optimization. No package includes unlimited usage.

Customer resources required
  • · API access + credentials for: PSS/reservations, Disruption management, Payments/refunds
  • · A named business owner for disruption rebooking and proactive passenger communication
  • · Security review counterpart and policy sign-off (PSS/reservations scope)
  • · Baseline metrics for the pilot's success thresholds
Executive messages

What to say to whom

CEO

“Air New Zealand's service reputation is a national asset under strain from capacity constraints; agentic disruption care protects the brand precisely where fleet issues make disruption more likely.”

CIO / CTO

“You've moved early on AI publicly; adding a Gemini-powered frontline for voice and disruption gives you best-of-breed pluralism and a live benchmark across platforms.”

COO

“You cannot staff Auckland for February's worst day; elastic multilingual capacity absorbs the summer surge and the fog days without carrying the cost through winter.”

GM Customer Care & Loyalty

“Proactive rebooking in the passenger's own language turns your hardest days into loyalty stories — and deletes the refund-status tail that clogs your queues for weeks after.”

Chief Risk / Compliance Officer

“NZ Privacy Act and Australian Privacy Act-aligned handling, full interaction logging and human gates on compensation — governance sized for a flag carrier's public accountability.”

CFO / Procurement

“A Launch-scoped pilot fits a mid-sized carrier's envelope, and the ROI is concrete: surge-staffing cost avoided plus saved rebookings, measured in one summer season.”

Outreach

Pre-built offer emails for Air New Zealand

Written from this account's own research — the strategic signal, the capability gap, the entry workflow, and the modelled economics — not a mail-merge template. Pick the moment and the persona, edit anything, then copy or open in your mail client.

Moment in the deal
Cold outreach — no prior conversation
Who it's addressed to
Cares about: The workflow itself and its daily failure modes
Register
Length
Draft — edit freely before sending
Open in mail client

Customer-safe by construction: drafts are composed only from customer-facing fields. Account tier, build-vs-buy classification, priority score, internal routing, and partner-commercial detail are not inputs to the composer, so they cannot appear in a draft. Money figures are always framed as modelled from the customer's own volumes. Read before sending — you own what goes out.

The pursuit

Tier 3 — longer-term / partner-led

Why this tier

A beloved flag carrier whose tourism-dependent, long-haul network concentrates risk in seasonal disruption spikes — smaller absolute volume than the majors, and an existing public OpenAI collaboration means the entry is a focused, benchmarkable workflow, not a platform pitch.

Recommended next step

Pre-summer planning session with customer care: scope a Launch pilot on disruption rebooking and Mandarin/Japanese service, live before the December peak.

Entry: Disruption rebooking and proactive passenger communication · Launch package · 8–10 weeks to a live, measured pilot. Human fallback throughout; success thresholds agreed before build.

Start the pursuit

Research-based priority-account universe assembled from public information, market scale, communication volume, and solution fit. This is NOT an authoritative list of top Google Cloud customers; existing Google Cloud relationships are noted only where publicly reported. Validate every account with the account team before outreach.