CIS study plan

Map the ServiceNow platform architecture by labeling the roles of the instance, application nodes, database, and MID Server in a diagram you draw yourself.

Explain how the Now Platform supports AI capabilities by describing at least three platform-level AI services (e.g., Now Assist, predictive intelligence, virtual agent) and the data each consumes.

Demonstrate navigation of the platform UI by creating a personal developer instance and recording a 5-minute walkthrough of list views, forms, and the application navigator.

Define key platform terminology in your own words: table, record, field, dictionary entry, and update set.

Configure a custom table with at least five field types and explain how dictionary attributes affect form behavior.

Build a form layout and list view for your custom table, then verify role-based access by testing with two different users.

Compare ACL types (record, field, UI page) and write a short note on when each applies.

Trace how an update set captures configuration changes by moving one change from a sub-production to a personal instance.

Implement a client-side script (onChange or onSubmit) that validates a field and shows a message, then explain the client/server boundary.

Write a business rule that runs before insert and sets a default value, and test it with three record scenarios.

Automate a simple approval flow using Flow Designer with at least one trigger, action, and approval step.

Document the difference between business rules, script includes, and UI policies with one use case each.

Describe the ITSM core workflow by mapping incident, problem, and change states and the transitions between them.

Configure one SLA definition on the incident table and verify it triggers using a test record.

Explain how CMDB classes and relationships support impact analysis, using a three-tier service example you build.

Compare at least two ServiceNow products (e.g., HRSD and CSM) by their primary data model and user workflow.

Summarize the purpose and key tables of three additional products (e.g., ITBM/SPM, Security Operations, Field Service Management).

Trace a request from the service catalog through fulfillment by building one catalog item with a variable set and a flow.

Explain how workspace and portal experiences differ for end users and fulfillers, with one example of each.

Identify the reporting and dashboard options available across products and when to use performance analytics versus standard reports.

Explain how Now Assist and generative AI features are configured and governed, including the role of the AI Control Tower or equivalent governance controls.

Describe data classification and the implications of putting sensitive data into AI prompts or models.

Outline the data lifecycle in ServiceNow: ingestion, normalization, retention, and archiving.

List at least four governance controls (e.g., access control, audit logging, model review, data residency) and match each to a risk it mitigates.

Evaluate a dataset for AI readiness by checking completeness, consistency, and bias in a sample table you create.

Explain how predictive intelligence works at a high level: training, scoring, and retraining triggers.

Describe how platform AI features depend on platform fundamentals such as ACLs, CMDB accuracy, and data quality.

Draft three questions you would ask a stakeholder before enabling an AI feature in production.

Synthesize all domains by building one end-to-end scenario: a catalog request that creates a record, triggers a flow, updates the CMDB, and produces a report.

Review weak areas from prior weeks and close at least two gaps using official documentation and hands-on practice.

Complete a timed 60-question practice set across all domains and review every missed item.

Write a personal exam-day strategy covering time allocation and question triage.