The Complete Guide to ServiceNow GenAI & Agentic AI

Walkthrough of plugin activation using the Now Assist Admin Console.

Show how to enable and configure AI skills across domains.

Demonstrate the Now Assist side panel in the Next Experience UI.

Explain governance, guardrails, and monitoring of AI usage.

Cover incident assist, change risk, KB generation, and summarization in IT Service Management.

Demonstrate case summarization, email/chat assist, KB generation, and voice summaries in Customer Service Management.

Show how HR agents use Now Assist for KB and workspace support in Human Resources Service Delivery.

Explore alert analysis and investigation skills in IT Operations Management.

Use cases in incident summarization, recommendations, and RCA.

Cover project summaries, feedback analysis, and document generation in Strategic Portfolio Management.

Explain AI task closure summarization and KB support in Field Service Management.

Explain AI task closure summarization and KB support in Financial Service Operations.

Summarization of CI records and duplicate management.

How to create your own skills using the Now Assist skills kit

Demonstrate ServiceNow  app creation using GenAI.

Build catalog items faster with GenAI.

Generate code snippets, flows, and scripts with AI.

Build Flows faster with GenAI.

Use AI to generate data visualizations, reports and dashboards.

Explain AI agents in ServiceNow and their role in workflows.

Design, configure, and manage AI Agents wit AI Agent Studio

Build chained workflows with multiple agents.

How to Create an AI Agent with use case

Understand how the out of box ServiceNow AI Agents for ITSM are configured and see the ITSM Incident triage  AI Agent in action.

Explain the Knowledge Graph and its designer tool.

View and configure Knowledge Graph schemas

Show prebuilt KG integrations with Virtual Agent and Now Assist Agents.

Extract structured insights from PDFs and images.

Use ServiceNow Lens for visual understanding.

Explain admin and creator roles needed for Now Assist.

Show how to track AI activity with GenAI logs.

Share best practices for scaling AI adoption.

You will recognise what AI Control Tower is, why organisations without it are flying blind, and how it closes the gap between AI deployment speed and governance maturity. You will preview every tab you will configure and demonstrate in this section.

You will navigate the AI Control Tower Overview tab and identify the six core widgets: All AI Systems (lifecycle stage distribution), AI Systems by Type, Risk Classification, AI Systems by Provider, Compliance posture bar, and AI Cases by Priority. You will interpret what each widget signals — distinguishing between a healthy AI portfolio and one with governance gaps — using the NovaTech instance as your reference state.

You will differentiate the three primary AI Control Tower personas and configure the correct role assignments for the NovaTech team. You will apply the sn_ai_governance.ai_steward role to Diana Temple's administrator profile and understand how role scope controls what each persona sees — AI stewards see the full AI estate; product owners see only the assets they manage.

A theory lesson establishing how ServiceNow models AI as a first-class citizen of the CMDB. Covers the five AI artifact types (AI System, AI Model, Data Set, Prompt, Inputs and Outputs), the system-versus-model distinction, how records are built across the CSDM v5 lifecycle, and the four ingestion paths into the AI inventory (hyperscaler integrations, record producers, REST APIs, auto-discovery). Sets the conceptual foundation for the hands-on inventory and governance lessons that follow.

You will create and register three types of AI assets in the AI asset inventory: an AI system, an AI model, and a prompt. You will populate all governance metadata fields including asset type (Generative AI, Agentic AI, Classic AI), provider, department, managed-by owner, lifecycle phase, and state. You will also demonstrate the difference between managed and unmanaged assets and trigger the steward review workflow to transition an unmanaged asset into governed status.

You will walk through the complete AI asset lifecycle in ServiceNow: from New → Assess → Build and Test → Deploy → Offboarding. You will initiate a steward review for one of NovaTech's 35 newly added AI systems, action the approval playbook, approve the asset for development, and progress it to Ready for Deployment. You will configure the AI steward approval control that blocks deployment until review is complete.

You will explore the AI Asset Inventory tab and analyse its four widgets: AI Systems by Provider (donut chart), AI Systems by Type, All AI Systems by lifecycle stage, and AI Asset Inventory by Department (bar graph). You will apply the NovaTech scenario — mapping NovaTech's AI estate by department (IT, Field Operations, HR) and identifying which departments are over-exposed with unmanaged assets.

You will configure the AI Strategy tab by setting up strategic priorities and goals with the Artificial Intelligence category in ServiceNow Goal Framework, then verifying they surface in AI Control Tower. You will demonstrate the four sub-sections — Strategy, Costs, Prioritised AI Work, and AI RIDAC — showing how projects and demands with Investment type = Artificial Intelligence aggregate into the dashboard. Note: this tab requires a Strategic Portfolio Management Professional licence.

You will use the Value dashboard to identify the Top 5 AI Systems by value (hours saved), interpret the Productivity widget showing cumulative time savings from AI actions, and analyse Average AI Users and Daily AI Actions trends. You will connect value templates to NovaTech's deployed AI assets, demonstrating how the platform turns AI usage data into executive-ready ROI evidence.

You will analyse the Adoption dashboard's two tabs — Usage and Adoption — to identify departments with highest AI action volume, track daily unique users engaging with AI, review positive feedback percentages, and compare AI action volume by workflow. You will apply the NovaTech scenario: field engineering (Ashley's department) shows near-zero AI engagement while IT is at high utilisation — you will diagnose the gap and recommend corrective action.

You will configure the Risk and Compliance tab using the NIST AI Risk Management Framework as your authority document. You will navigate the four NIST AI RMF function citations (Map, Measure, Manage, Govern), review compliance attestation scores per citation, and drill into the risk heatmap to locate NovaTech's two high-risk AI systems. You will then configure the Risk Classification methodology and set up the EU AI Act as a secondary compliance framework alongside NIST.

You will create an AI case directly from the AI Control Tower dashboard — documenting a detected NIST compliance violation against one of NovaTech's deployed Generative AI systems. You will assign the case to an AI analyst, set priority to High, link it to the relevant AI asset, track it through its lifecycle states (New → Triage → In Progress → Resolved), and use the Trends widgets to monitor open vs closed case velocity over the past 12 months. You will also raise a linked AI issue from the case record.

Explore ServiceNow’s vision for autonomous operations.

Discuss bias, drift, and transparency.

Future-proofing skills and strategy.

Review course highlights and learner takeaways.

Point to Now Learning, Docs, and communities.