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ServiceNow Travel and Hospitality Europe

Booking.com

IT Operations Automation

Booking.com employees across HR, IT, Legal, and Finance had to navigate org charts and manual routing paths just to get help, causing misrouted tickets and slower resolution.

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33% Reduction in time to resolution
97% Of tickets correctly assigned
Booking.com’s AI agents get it right 97% of the time
Booking.com’s employees deserve the same seamless experience it delivers to 500 million travelers

Reported impact

Business outcome

Booking.com now routes tickets correctly 97% of the time, has cut resolution times by 33%, and operates one support platform for roughly 16,200 employees.

  • Customer Experience
  • Productivity Improvement

Solution

Booking.com employees across HR, IT, Legal, and Finance had to navigate org charts and manual routing paths just to get help, causing misrouted tickets and slower resolution. Booking.com implemented a ServiceNow-centered stack built around AI Agents, IT Service Management, HR Service Delivery, and CRM. Key components included AI Agents run AI-driven triage and response tasks; IT Service Management standardizes incidents and requests; HR Service Delivery manages HR cases and onboarding; CRM contributes account and opportunity context. The stack also connected Legal and Finance so the workflows could reuse existing records, documents, and collaboration channels instead of forcing teams back into manual handoffs. Work enters as cases, requests, or automations, is classified or summarized by AI Agents, and uses context from CRM, Legal, and Finance before IT Service Management and HR Service Delivery routes or fulfills the work.

Data flow

Work enters as cases, requests, or automations, is classified or summarized by AI Agents, and uses context from CRM, Legal, and Finance before IT Service Management and HR Service Delivery routes or fulfills the work. The same record of work is then exposed back to agents and end users through the platform.

Solution architecture

4 components · 3 layers
  1. Compute
    • AI Agents Execute AI-driven routing, triage, and response tasks inside support workflows.
  2. Storage
    • CRM Contributes customer, opportunity, or account context into ServiceNow workflows.
  3. Orchestration
    • IT Service Management Standardizes incident, request, and fulfillment workflows on the platform.
    • HR Service Delivery Moves HR cases, onboarding, and employee support workflows onto the same platform.

Evidence from the source

Booking.com’s AI agents get it right 97% of the time The behind the ‘Connected Trip’ is now building the Connected Employee—one platform unifying HR, IT, Legal, and Finance for 16,200 people 33% Reduction in time to resolution 97% Of tickets correctly assigned Booking.com’s employees deserve the same seamless experience it delivers to 500 million travelers Booking.com is obsessed with the seamless travel experience
The Automatic Ticket Classification Agent tackled a different problem in HR
The agent now reads intent, detects sentiment and urgency, and routes 97% of tickets to the correct team, correct priority, and correct service catalog item—on the first pass, without human intervention
The next milestone is AI Control Tower —centralized visibility across every AI use case, from lifecycle status to ROI tracking to asset inventory
Vipul Hingne Interim CTO, Booking.com AI took over the routine work, so Booking.com’s people could focus on the work that matters With a unified platform in place, Booking.com identified workflows where talented people were doing repetitive, low-value work at scale
Transparency Evidence & methodology 95/100 reference value · 79% confidence · 1 source

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth20/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    5 direct source quotes retained.
  • Date provenance0/10
    The publication date has no documented provenance.
  • Source transparency8/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. ServiceNow

    Booking.com customer story

    First-party
    https://www.servicenow.com/customers/booking.html
    Source type
    Vendor-published customer story
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes

Date evidence

  • First archived Jul 21, 2026 · Internet Archive · Independent First Wayback Machine capture; confirms the page existed by this date, not when it was published.
    Open date source
  • Sitemap last modified Aug 3, 2026 · ServiceNow · Publisher metadata Publisher-reported modification timestamp; not a publication date.
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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