Reported impact
Business outcome
Adobe cut case-resolution time by 30%, reduced outage-resolution time by 25%, and expects email-triage processing time to fall by 96% as automation expands.
- Customer Experience
- Productivity Improvement
ServiceNowSoftware / SaaSIT Operations AutomationAI and Machine LearningERP / CRMGenerative AI / LLMCustomer ExperienceProductivity ImprovementUndated ServiceNowSN#1f8476Software / SaaSNorth AmericaAdobe had fragmented support systems that made it harder to trace issues, support onboarding, and move work consistently across IT, HR, security, workplace, and customer-care teams.25% Less time to resolve outagesArchived · Jan 14, 20265IT Operations AutomationAI Agents · HR Service Delivery · IT Service Management0 2026-01-14 5
Adobe
IT Operations Automation
Adobe had fragmented support systems that made it harder to trace issues, support onboarding, and move work consistently across IT, HR, security, workplace, and customer-care teams.
25% Less time to resolve outages
30% Faster case resolutions
96% Planned reduction in processing time through email triage
Adobe IT and HR move 30% faster so teams can dream bigger
Solution
Adobe had fragmented support systems that made it harder to trace issues, support onboarding, and move work consistently across IT, HR, security, workplace, and customer-care teams. Adobe implemented a ServiceNow-centered stack built around ServiceNow AI Platform, AI Agents, IT Service Management, and HR Service Delivery. Key components included ServiceNow AI Platform provides the common workflow and AI layer; AI Agents run AI-driven triage and response tasks; IT Service Management standardizes incidents and requests; HR Service Delivery manages HR cases and onboarding. Requests enter through Virtual Agent, are classified or summarized by AI Agents before ServiceNow AI Platform, 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. Running employee support and operational workflows on one data model reduced manual handoffs and made expansion easier.
Data flow
Requests enter through Virtual Agent, are classified or summarized by AI Agents before ServiceNow AI Platform, 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
- Compute
- AI Agents Execute AI-driven routing, triage, and response tasks inside support workflows.
- Serving
- Virtual Agent Handles conversational self-service and ticket deflection for users.
- 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.
- HR Service Delivery Moves HR cases, onboarding, and employee support workflows onto the same platform.
Evidence from the source
AI Agents that helps Adobe IT and HR move 30% faster so teams can dream bigger
Before, with limited visibility into fragmented systems, any lag or errors could be hard to track down
By uniting services on a single platform, Adobe can turn disconnected data and workflows into simple, end-to-end processes
For IT and HR teams, using AI capabilities with ServiceNow means even faster resolutions that help employees get back to the work they love
More than 8,000 IT and HR team members take advantage of generative AI, using Now Assist to summarize complex cases and write resolution notes
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 impact25/254 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/adobe.htmlServiceNowFirst-party
Adobe 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 Jan 14, 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 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.
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