Reported impact
Business outcome
Teleperformance increased IT Service Desk automation by 38%, improved deflection by 10%, raised end-user CSAT by 8%, and saved 15-25 minutes per major incident.
- Customer Experience
- Productivity Improvement
ServiceNowCommercial and Professional ServicesIT Operations AutomationAI and Machine LearningContact CenterGenerative AI / LLMCustomer ExperienceProductivity ImprovementUndated ServiceNowSN#1f8476Commercial and Professional ServicesGlobalTeleperformance was running six separate IT ticketing platforms worldwide, which made multilingual service delivery, automation, and orchestration across its internal service desk difficult.10% Improvement in internal IT Service Desk deflection rateArchived · Mar 31, 20255IT Operations AutomationEmployee Center · IT Service Management · Now Assist0 2025-03-31 5
Teleperformance
IT Operations Automation
Teleperformance was running six separate IT ticketing platforms worldwide, which made multilingual service delivery, automation, and orchestration across its internal service desk difficult.
10% Improvement in internal IT Service Desk deflection rate
15 - 25 Minutes saved per major incident
Solution
Teleperformance was running six separate IT ticketing platforms worldwide, which made multilingual service delivery, automation, and orchestration across its internal service desk difficult. Teleperformance implemented a ServiceNow-centered stack built around ServiceNow AI Platform, IT Service Management, Virtual Agent, and Employee Center. Key components included ServiceNow AI Platform provides the common workflow and AI layer; IT Service Management standardizes incidents and requests; Virtual Agent handles conversational self-service; Employee Center provides a single employee portal. Requests enter through Virtual Agent and Employee Center, are classified or summarized by Now Assist before ServiceNow AI Platform and IT Service Management routes or fulfills the work. The same record of work is then exposed back to agents and end users through the platform. Running employee support and operational workflows on one data model reduced manual handoffs and made expansion easier.
Data flow
Requests enter through Virtual Agent and Employee Center, are classified or summarized by Now Assist before ServiceNow AI Platform and IT Service Management routes or fulfills the work. The same record of work is then exposed back to agents and end users through the platform.
Solution architecture
- Compute
- Now Assist Adds generative-AI capabilities such as summarization, drafting, search, and guided responses inside workflows.
- Serving
- Virtual Agent Handles conversational self-service and ticket deflection for users.
- Employee Center Serves a single portal for requests, knowledge, and support interactions.
- Orchestration
- ServiceNow AI Platform Acts as the common workflow and AI platform that unifies service data, automation, and user experiences.
- IT Service Management Standardizes incident, request, and fulfillment workflows on the platform.
Evidence from the source
It helps organizations optimize their performance and customer experience with interactions that are simpler, faster, and safer
TP believes that AI enables its employees to deliver more empathy, which is one of the reasons why the organization prioritized productivity for its IT Service Desk experts
The TP difference is that AI shouldn’t be seen as a productivity tracker, it must be an enabler of human empathy
With ServiceNow AI tools and capabilities, associates can get back up and running faster and continue delivering exceptional experiences to our clients
Worldwide, it had been using six different IT ticketing platforms, making it difficult to drive consistent automation, and a challenge to orchestrate IT services
Transparency Evidence & methodology
Review how this reference was scored and trace each normalized claim back to its documented source.
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 value90/100
- Problem clarity20/20Measures whether the customer's operational problem is specific enough to compare.
- Implementation depth15/25Rewards named components, data flow, integrations, and architecture detail.
- Outcome specificity20/20Measures whether the reported benefit is concrete rather than a generic claim.
- Quantified impact25/252 metrics describe measurable impact.
- Deployment scale10/10Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence79%
- Source authority20/25The main evidence is an official vendor-published customer story.
- Claim traceability21/2510 of 12 key fields link to a named source.
- Direct evidence20/205 direct source quotes retained.
- Date provenance0/10The publication date has no documented provenance.
- Source transparency8/101 source reference document publisher, URL, authority, retrieval, and supported fields.
- Implementation specificity10/10Rewards source-backed components, data flow, quantified impact, and a specific outcome.
Traceability
Sources & provenance
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
- https://www.servicenow.com/customers/teleperformance.htmlServiceNowFirst-party
Teleperformance 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 Mar 31, 2025 · 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 Jul 30, 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.
Related
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