01
ServiceNow AI Platform & Enterprise Workflow Foundations
Understand what the ServiceNow AI Platform is in 2026–2027, how it differs from a ticketing tool, and where each role contributes.
Core Platform & ITSM
SaaS, PaaS and enterprise workflow platforms
Platform architecture and the Australia-release capability map
People, workflows, data, applications, integrations, AI and governance
Deterministic automation, generative assistance and agentic execution
Now Assist, Otto, EmployeeWorks and Autonomous Workforce concepts
Platform roles and separation of duties
PDI, customer instance and production-shaped lab distinctions
Release cadence, Store applications and entitlement awareness
HANDS-ON LAB
Provision the approved learner instance, inspect installed applications, identify unavailable capabilities and create a platform capability inventory.
WORKPLACE SCENARIO
A sponsor describes ServiceNow as "the IT ticket tool" while asking the team to automate onboarding across HR, IT, facilities and identity systems.
LEARNER SHIPS
Instance & entitlement inventory
Platform capability map
Role & responsibility map
Learning-path decision
Limitations statement
Assessed gate · Explain the platform without marketing slogans, map three enterprise scenarios to the 20-module journey and identify any readiness bridge required.
02
Instance, Navigation, Tables & Platform Data
Build the data and configuration foundation required for secure workflow applications.
Core Platform & ITSM
Next Experience navigation, lists, forms, filters and search
Tables, records, fields and sys_id; base, extended and custom tables
Extension versus reference decisions
Dictionary, schema map, field types and reference qualifiers
Data policies, import sets, transform maps and validation
Configuration versus customisation; scoped-application boundaries
Update sets, application repository and deployment context
Data quality, ownership and retention
HANDS-ON LAB
Create the data foundation for an Employee Service Request application with request, task, service, approval and evidence relationships.
WORKPLACE SCENARIO
Two teams independently create employee and department tables even though governed platform sources already exist.
LEARNER SHIPS
Logical data model
Configured tables & fields
Schema map
Import/validation evidence
Ownership register
Technical-debt note
Assessed gate · Defend extension, reference and reuse decisions and prove that imported records meet defined quality rules.
03
Users, Groups, Roles, ACLs & Platform Security
Apply identity and least-privilege controls to users, fulfiller teams, application services and future AI actors.
Core Platform & ITSM
Users, groups, roles and role inheritance
ACL operations and evaluation; table, record and field access
Scripted and condition-based ACLs; user criteria
Impersonation and access debugging
Privileged roles and separation of duties
Service and integration identities; secrets management
AI-agent identities, dynamic users and role masking
Audit events and secure-by-default design
HANDS-ON LAB
Implement requester, fulfiller, manager approver, auditor and integration access for the core application; test positive and negative cases.
WORKPLACE SCENARIO
An AI-assisted workflow inherits the invoking administrator’s broad permissions and can read HR fields outside the task’s scope.
LEARNER SHIPS
Role catalogue
Access-control matrix
Implemented ACLs
Impersonation test evidence
AI identity boundary design
Assessed gate · Demonstrate that each persona can perform required work and cannot access prohibited data or actions.
04
ITIL, Workflow Discovery, Incident & Major Incident Operations
Use ITIL and discovery evidence to design and operate an incident service that restores value and creates trustworthy operational learning.
Core Platform & ITSM
Services, value streams and ITIL 4 foundations
Interviews, workshops, observation and current-state blueprints
Impact, urgency, priority and assignment models
Major-incident declaration, communications and review
Service-level and operational-level commitments
Agent workspace, swarming and cross-team collaboration
Now Assist and AI-agent triage, summarisation and guided resolution
Requirements, acceptance examples and traceability
HANDS-ON LAB
Run discovery for a degraded employee-access service and configure a controlled incident-to-resolution flow with priority, assignment, major-incident escalation and bounded AI-assisted triage.
WORKPLACE SCENARIO
A monitoring signal and multiple employee reports describe the same outage — duplicate records, weak service context and an unverified AI summary could misdirect responders.
LEARNER SHIPS
Stakeholder map & discovery notes
Current & future workflows
Configured incident workflow
AI-triage authority boundary
SLA dashboard & runbook
Assessed gate · Discover and triage an unseen incident, justify priority and escalation, restore service and distinguish verified facts from AI-generated suggestions.
05
ITSM: Problem, Change, Request, Catalog, Knowledge & Continual Improvement
Reduce repeat failure, govern service change and convert employee demand into reusable, measurable fulfilment services.
Core Platform & ITSM
Problem investigation, root cause, known errors and workarounds
Change models: standard, normal and emergency; risk and conflict
CAB responsibilities, implementation, validation and backout
Catalog items, variables, record producers and order guides
Fulfilment models, approvals, entitlements and sensitive-data controls
SLAs, calendars, pauses and breaches
Knowledge lifecycle and Employee Center self-service
AI assistance for clustering, risk signals and fulfilment
HANDS-ON LAB
Investigate recurring access incidents, create a problem and known error, design a governed change, then build an employee-access catalog request end to end.
WORKPLACE SCENARIO
An AI recommendation labels a risky change "low risk," while the related catalog item grants broad access, exposes confidential variables and lacks tested backout.
LEARNER SHIPS
Problem & root-cause dossier
Change model & backout
Catalog item & fulfilment workflow
Knowledge article
Post-implementation review
Assessed gate · Approve, constrain, reschedule or reject a change and complete success, rejection, timeout and unauthorised-access request cases using traceable evidence.
06
Flow Designer, Workflow Studio & Agentic Automation
Implement maintainable deterministic automation, then introduce agentic decisions only where authority, evidence and recovery controls are explicit.
Platform Engineering & AI
Triggers, actions, subflows and flow data
Conditions, decisions, loops, waits and approvals
Error handling, compensation and human escalation
Idempotency and duplicate-execution protection
Flow Designer and Workflow Studio roles; playbooks
Deterministic workflow versus AI-agent allocation
Tool/action permissions, identity and stop conditions
Execution details, traces and troubleshooting
HANDS-ON LAB
Automate the access-request and incident handoff with reusable subflows, external-action simulation, timeout handling, compensation and one bounded agentic decision.
WORKPLACE SCENARIO
A retry creates duplicate fulfilment work while an agent proceeds after its confidence and authority boundary should have triggered human escalation.
LEARNER SHIPS
Automated workflow
Reusable subflow/action
Human–AI allocation record
Tool-authority matrix
Execution traces & runbook
Assessed gate · Prove correct behaviour under success, rejection, timeout, duplicate, low-confidence and unauthorised-action conditions.
07
JavaScript, Glide APIs & Maintainable Scripting
Use code only where it adds necessary capability — and write it in a secure, reusable, observable and testable way.
Platform Engineering & AI
JavaScript essentials, execution contexts and application scope
Client Scripts, UI Policies and g_form
Business Rules, order of execution and recursion risks
Script Includes and reusable service layers
GlideRecord, GlideAggregate and query discipline
GlideAjax and client/server communication
Secure coding, injection risks, performance and bulk work
AI-assisted code generation with independent verification
HANDS-ON LAB
Implement a reusable entitlement-validation Script Include, call it safely from client and server contexts, add deterministic tests and refactor an inefficient query.
WORKPLACE SCENARIO
A synchronous lookup slows every form load, a Business Rule recursively updates the same record and generated code omits a role-negative case.
LEARNER SHIPS
Reviewed scripts
Reusable Script Include
Deterministic tests
Performance comparison
AI-assistance provenance
Assessed gate · Debug an unseen defect, explain the platform execution model and defend why code or a declarative alternative is safer.
08
Scoped Applications, Studio, IDE, Build Agent & Source Control
Build and version a maintainable scoped application using current UI-first and code-first paths, including responsible agentic development.
Platform Engineering & AI
Application scope and architecture
ServiceNow Studio, IDE and SDK/Fluent concepts
Build Agent planning, checkpoints, diffs and rollback
Agentic development versus contextual assistance
Review of AI-generated metadata and code
Generated tests and independent verification
Branch, review and merge practices
Licensing, patch and model availability
HANDS-ON LAB
Build a Safety Incident Management application; use Build Agent for one bounded change, inspect the plan and diff, test it and document human corrections.
WORKPLACE SCENARIO
Build Agent creates working functionality but duplicates a platform field, broadens a role and misses a failure condition.
LEARNER SHIPS
Scoped application
Source repository
Build Agent provenance record
Reviewed diffs
Deployment package
Technical-debt register
Assessed gate · Explain every delivered component and reverse or correct an unsafe AI-generated change.
09
UI Builder, Workspaces & Human–AI Experience
Create a role-aware, accessible experience in which people can complete work, understand AI assistance and recover from errors.
Platform Engineering & AI
Next Experience and workspace concepts
UI Builder pages, variants, routing and components
Data resources, bindings and client state
Human–AI interaction: evidence, uncertainty and explanation
Action preview, consent and approval
Correction, feedback and escalation
Loading, timeout and degraded states
WCAG 2.2 AA, keyboard and screen-reader requirements
HANDS-ON LAB
Build an Employee Service Operations workspace showing incident/request context, recommendation evidence, action preview, approval, audit status and safe fallback.
WORKPLACE SCENARIO
Users approve an AI-prepared access change without seeing which entitlements will be granted, and keyboard-only users cannot open the evidence panel.
LEARNER SHIPS
User journey
Role-based workspace
AI evidence/approval pattern
Accessibility test
Usability findings
Assessed gate · Representative users complete the workflow, understand what the system will do and recover without hidden trainer assistance.
10
ServiceNow Enterprise Integrations
Connect ServiceNow to enterprise applications, data sources and action systems through secure, resilient and governed integration patterns.
Platform Engineering & AI
Inbound, outbound, synchronous, asynchronous and event-driven patterns
Table, Import Set and Scripted REST APIs
OAuth, credentials, connection aliases and secrets
Integration Hub spokes and custom actions; MID Server
Workflow Data Fabric, Zero Copy concepts and governed data products
Retries, timeouts, rate limits, idempotency and duplicate prevention
Partial failure, compensation and reconciliation
API lifecycle, versioning and consumer contracts
HANDS-ON LAB
Integrate the employee-service solution with simulated identity and policy systems, package authoritative attributes as a governed data product and implement retry, idempotency, reconciliation and alerting.
WORKPLACE SCENARIO
The identity API accepts requests asynchronously, returns an uncertain status and processes a duplicate retry that creates a conflicting entitlement.
LEARNER SHIPS
Integration landscape
Interface & data contracts
Reusable integration action
Reconciliation & recovery evidence
Operations runbook
Assessed gate · Trace a cross-system transaction, detect partial failure, prevent duplicate action and restore a consistent state without exposing credentials.
11
ServiceNow CSDM & CMDB
Create trustworthy service and configuration context for ITSM, ITOM, ITAM, integrations, analytics and AI-assisted decisions.
Platform Engineering & AI
CMDB purpose, CIs, classes, attributes and relationships
Identification and reconciliation rules
Duplicate, stale, orphan and incomplete CI controls
CMDB Health, certification, ownership and remediation
CSDM domains, maturity, services and offerings
Service Graph connectors, Discovery and Service Mapping relationships
Authoritative sources, provenance, freshness and withdrawal
Context Engine concepts and role-appropriate context
HANDS-ON LAB
Model the employee-access service, its business application, application service, technical dependencies and service offering; configure health and context-quality gates.
WORKPLACE SCENARIO
An operations workflow and AI recommendation use a stale CI owner, duplicate application records and an incomplete service relationship to estimate impact.
LEARNER SHIPS
CSDM-aligned service model
Identification/reconciliation rules
Source-authority matrix
CMDB Health baseline
Context-quality policy
Assessed gate · Demonstrate which context is authoritative, how it is reconciled and what happens when quality falls below an operational or AI-use threshold.
12
ServiceNow Testing & DevOps
Build independent release evidence and operate a controlled delivery lifecycle across configuration, code, workflows, integrations and upgrades.
Platform Engineering & AI
Risk-based quality strategy
ATF architecture, reusable tests, suites, test data and cleanup
Form, server, API, flow and workspace testing
Positive, negative, permission and failure-path cases
Review of Build Agent / Test Agent-generated tests
Source control, CI/CD pipelines and environment promotion
Clones, family upgrades, skipped changes and regression
DevSecOps controls, segregation of duties and audit evidence
HANDS-ON LAB
Create a release dossier for the scoped application with an ATF suite, integration and accessibility tests, pipeline gates, upgrade regression and a rollback exercise.
WORKPLACE SCENARIO
AI-generated tests pass because they repeat the builder’s incorrect assumption, a negative ACL case is absent and an upgrade introduces a skipped change.
LEARNER SHIPS
Quality & test strategy
ATF suite & evidence
UAT traceability
CI/CD & release design
Rollback & recovery evidence
Assessed gate · Make and defend a release decision when average results look strong but one high-consequence permission or recovery case fails.
13
ServiceNow AI: Now Assist, AI Agents & AI Control Tower
Design, build, evaluate, release and govern AI-assisted and agentic workflows as accountable platform assets.
Platform Engineering & AI
Predictive, generative and agentic AI boundaries
Now Assist experiences, grounding and human verification
AI Agent Studio, Orchestrator, goals, tools, memory and stop conditions
Action Fabric and MCP governance; AI Gateway and provider policy
AI identities, dynamic users, role masking and least privilege
Agentic evaluation datasets, versions, metrics and traces
Prompt-injection, excessive-action, privacy and security testing
AI Control Tower: Discover → Observe → Govern → Secure → Measure
HANDS-ON LAB
Build and evaluate a bounded service-operations agent that retrieves governed context, summarises evidence, recommends a next step and executes only one approved low-risk action.
WORKPLACE SCENARIO
Average evaluation results are high, but one permission test shows the agent can act on a restricted record and no tested kill switch exists.
LEARNER SHIPS
AI use-case & autonomy decision
Tool & identity matrix
Versioned evaluation dataset
Kill-switch design
Control Tower registration pack
Value scorecard
Assessed gate · Make and defend a release, constrain, defer, rollback or stop decision when safety, evidence, value and operational-readiness signals disagree.
14
Customer Service Management (CSM)
Connect customer service to enterprise fulfilment so issues are resolved through governed workflows, not merely recorded as cases.
Enterprise Product Domain
CSM operating model; accounts, contacts, consumers and installed base
Interactions, cases, case types and lifecycle
Entitlements, service contracts and service-level commitments
Assignment, queues, skills and agent workspace
Self-service, portals, knowledge and conversational channels
Major issue, complaints, escalations and proactive communication
Customer-service AI agents with consent and privacy boundaries
Integration with ITSM, ITOM, Sales CRM and external systems
HANDS-ON LAB
Configure an AI-assisted customer case for a degraded subscription service — entitlement check, knowledge, service-team handoff, major-issue communication and closure validation.
WORKPLACE SCENARIO
A customer-facing agent promises an action outside the customer’s entitlement while the underlying outage belongs to an IT operations team.
LEARNER SHIPS
Customer-service blueprint
Configured case journey
Entitlement & escalation rules
AI-agent boundary
Value/adoption scorecard
Assessed gate · Resolve an unseen case across customer service and IT operations without exposing internal-only data or allowing AI to exceed contractual authority.
15
ServiceNow Sales CRM
Create a connected, AI-guided revenue workflow from lead qualification through opportunity progression while preserving commercial controls.
Enterprise Product Domain
ServiceNow CRM and Sales Automation positioning
Leads, accounts, contacts, opportunities and activities
Qualification criteria and lead conversion
Opportunity stages, next steps, probability and evidence
Seller workspace, forecasting and pipeline hygiene
AI agents for research, qualification, preparation and follow-up
Hallucination, consent, outreach and record-provenance controls
Handoffs to CPQ, order management, fulfilment and CSM
HANDS-ON LAB
Build a lead-to-opportunity journey with qualification rules, a seller workspace, AI-assisted meeting preparation and a governed handoff to customer onboarding.
WORKPLACE SCENARIO
An AI sales agent enriches an account with unverified data, advances the stage without evidence and drafts an outreach action outside approved policy.
LEARNER SHIPS
Sales-process blueprint
Lead & opportunity workflow
Seller workspace
AI-sales authority policy
Pipeline dashboard
Assessed gate · Qualify and progress an unseen opportunity using traceable evidence, correct authority and an auditable customer handoff.
16
HR Service Delivery (HRSD)
Deliver secure, human-centred employee services across HR, IT and workplace systems while protecting sensitive workforce data and decisions.
Enterprise Product Domain
HRSD operating model, HR profiles and Centres of Excellence
HR services, cases, tasks and case confidentiality
Employee Center and conversational self-service
Employee journeys and lifecycle events, hire to retire
HR agent workspace, assignment and escalation
Now Assist and HR AI-agent opportunities
Policy grounding, human review and workforce-decision boundaries
Privacy, legal hold, role separation and audit
HANDS-ON LAB
Configure a new-hire journey with secure HR case handling, employee self-service, IT access and asset tasks, policy evidence and a bounded AI assistant.
WORKPLACE SCENARIO
An AI agent can infer sensitive employee information and attempts an eligibility decision that policy reserves for an authorised HR professional.
LEARNER SHIPS
Employee-service blueprint
HR data/security matrix
Configured case & journey
AI & human-decision boundary
Privacy test evidence
Assessed gate · Complete a hire-to-productive journey while proving confidentiality, correct handoffs, human accountability and recoverability.
17
IT Asset Management (ITAM)
Manage hardware, software and cloud-asset lifecycles as connected cost, compliance, risk and service workflows.
Enterprise Product Domain
Asset versus configuration-item distinction
Request, procure, receive, stock, assign, maintain, reclaim and retire
Software entitlements, normalisation and compliance concepts
Contracts, vendors, warranties and renewals
Stockrooms, audits and chain of custody
Onboarding/offboarding and asset recovery
AI-agent opportunities for lifecycle tasks and audit response
Approval, disposal, data-erasure and evidence controls
HANDS-ON LAB
Configure a laptop lifecycle from approved request through receipt, assignment, repair, return, secure disposal and CMDB reconciliation.
WORKPLACE SCENARIO
An offboarded employee retains a device, discovery reports conflicting ownership and an AI agent proposes retirement before required data-erasure evidence exists.
LEARNER SHIPS
Asset-lifecycle blueprint
Asset/CI reconciliation model
Custody controls
AI authority boundary
Cost/risk dashboard
Assessed gate · Resolve an asset exception while preserving ownership, financial, security, CMDB and disposal evidence.
18
IT Operations Management (ITOM)
Turn infrastructure and application signals into service-aware detection, prioritisation and resilient operational action.
Enterprise Product Domain
Visibility-to-action lifecycle; MID Server architecture
Discovery patterns, credentials and schedules
Service Mapping and dynamic service context
Event Management, alert correlation and noise reduction
AIOps, anomaly detection and probable-cause concepts
Remediation, runbooks and bounded automation
ITOM–ITSM incident and change integration
False-positive, excessive-action and rollback controls
HANDS-ON LAB
Model a service-aware operations flow that correlates simulated alerts, identifies business impact, creates or updates an incident and proposes a governed remediation.
WORKPLACE SCENARIO
An AIOps correlation suppresses a signal that affects a critical business service, while autonomous remediation would restart the wrong component.
LEARNER SHIPS
ITOM architecture
Service map
Event-to-incident workflow
AI-operation authority matrix
Service-health dashboard
Assessed gate · Diagnose and respond to an unseen service degradation using trustworthy topology, correct priority and tested rollback.
19
Strategic Portfolio Management (SPM)
Connect strategy, demand, investment, capacity and delivery so the Platform Owner can make evidence-based portfolio decisions.
Enterprise Product Domain
Strategy-to-outcome operating model; goals and targets
Ideas, demands, initiatives and prioritisation
Roadmaps, dependencies and scenario planning
Investment, funding and capacity concepts
Business case, value hypothesis, cost, risk and confidence
AI-initiative inventory and AI Control Tower connection
Benefit attribution, stop decisions and value reviews
Platform Board cadence and decision rights
HANDS-ON LAB
Build and prioritise a portfolio containing ITSM, CSM, HRSD and agentic-AI initiatives under fixed capacity, risk and value constraints.
WORKPLACE SCENARIO
Every sponsor marks the initiative critical, estimated benefits use incompatible assumptions and the AI proposal lacks data-readiness evidence.
LEARNER SHIPS
Strategy/outcome map
Demand intake & scoring model
Portfolio & roadmap
Scenario decision
Executive portfolio briefing
Assessed gate · Fund, sequence, constrain, defer or stop initiatives and defend the decision under changing strategy, capacity and risk.
20
Governance, Risk & Compliance / Integrated Risk Management
Embed governance, risk, compliance and continuous assurance into daily enterprise workflows, including the lifecycle of AI assets.
Enterprise Product Domain
GRC and IRM operating model, entities and ownership
Risk statements, assessments, appetite and treatment
Policies, standards, controls and authority documents
Indicators, monitoring and continuous assurance
Issues, remediation, exceptions and audit evidence
Third-party risk and operational-resilience concepts
AI risk classification and AI asset inventory
Executive risk reporting and accountable acceptance
HANDS-ON LAB
Create a control and assurance pack for the programme’s AI-assisted access workflow, linking risks, controls, tests, issues, evidence, owners and remediation.
WORKPLACE SCENARIO
An AI asset is delivering value but uses an unapproved provider, lacks current evaluation evidence and has no named risk-acceptance authority.
LEARNER SHIPS
Risk/control library
Continuous-assurance indicators
AI-risk register
Executive risk decision
Cross-programme evidence index
Assessed gate · Approve, conditionally accept, remediate, suspend or retire an AI-enabled workflow using traceable risk, control, test and ownership evidence.
Honest scope — each enterprise product module (14–20) creates operating-model fluency and a working implementation slice, not full CIS-level product mastery. Product depth lives in optional follow-on specialisations (Administrator, Developer, ITSM/ITOM, HRSD, CSM/Sales CRM) published separately.