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ServiceNow AI Implementation (SNAII)
- Categories:
- Service Management
- Level:
- Fundamentals
- Code:
- QASNAIIIMPLE
- Exam:
- Not Applicable
Overview
This course gives you a practical introduction to implementing, managing, customizing, and governing AI-powered solutions on the ServiceNow AI Platform. It's designed for Implementers, System Administrators, Application Developers, and AI Practitioners who want to deploy generative and agentic AI capabilities, create workflows, and extend ServiceNow with advanced functionality.
By the end of the course, you'll be able to design, implement, and scale AI solutions in the platform with confidence, technical depth, and a strong grounding in governance best practices.
Prerequisites
To ensure you’re prepared for the advanced material in this course, the following courses are strongly recommended:
- Application Development Fundamentals
- Common Service Data Model (CSDM) Fundamentals
Target Audience
This course is ideal for ServiceNow Administrators, AI Stewards, Application Developers, and IT Professionals who implement and manage ServiceNow's AI capabilities.
What's included
Select your preferred way to learn:
What is Classroom?
Hands-on, instructor-led training delivered in a QA learning centre
In-person training in a dedicated QA learning centre. Learners benefit from expert-led sessions, collaborative activities, and structured, hands-on workshops in a distraction-free environment. If you can’t attend in person, many classroom courses are also available to attend remotely.
Classroom sessions can be arranged on request. Please contact your account manager to discuss availability in your region
Best for: Individuals and teams who benefit from deep focus, direct interaction, and practical, hands-on learning.
What's included?
2 Days instructor led course
Exam: Not Applicable
6 month free access to QA learning platform
Free 6-Month Access: Learning Platform Discovery plan
Included FREE with every instructor‑led course
Get free guided access to the QA Learning Platform. Assess your skills, explore in-demand topics, and understand which areas to focus on.
Learn AI, Cloud, Data, and Leadership skills at your own pace.
Put skills into practice with hands-on Labs and Simulabs.
Validate knowledge and highlight gaps with skills assessments.
What is bespoke training?
Custom instructor-led training designed by QA to fit your needs
Tailored programmes built around your organisation’s goals, challenges, and skill levels. Delivered in the format that suits you to maximise relevance and impact.
Best for: Organisations and teams looking to target specific business priorities and capabilities with QA subject matter expertise.
Find out more about the course:
Learning outcomes
- Understand foundational AI and Generative AI concepts and their relevance to ServiceNow.
- Evaluate organizational readiness for AI implementation, including data, foundational applications, and governance.
- Identify the components of the Now Assist framework and configure AI-powered end-user experiences.
- Explain ServiceNow’s model provider strategy and how models are selected, routed, and governed.
- Administer Now Assist deployments and manage settings through the Admin Console.
- Implement governance and responsible AI controls using the Now Assist Guardian capabilities.
- Extend the platform by building custom AI Skills with the Now Assist Skill Kit.
- Design and implement Agentic Workflows and AI Agents to automate and accelerate business processes.
- Enable cross-platform Agentic interaction using Agentic Fabric and the Model Context Provider (MCP) protocol.
- Monitor AI adoption, utilization, and value in the AI Control Tower.
Course outline
Module 1: Introduction to Generative AI
Objectives
This module introduces the fundamentals of AI and its impact on the enterprise. You’ll explore the evolution from rule-based systems to Generative AI, learn key concepts such as models, prompts, training, and inference, and examine the risks and responsibilities of GenAI. The module also highlights how the Now Platform enables AI-powered business transformation across workflows.
Lab work
Prepare for a Now Assist implementation
Module 2: Now Assist Data Readiness
Objectives
In this module, you’ll learn how to assess data and application readiness and estimate the effort required to implement Now Assist and Agentic Workflows in your platform. You’ll use guided checklists and practical evaluation criteria to verify that key components—such as the Knowledge Base, AI Search, Service Catalog, and Virtual Agent—are correctly configured and identify and address any gaps that could impact AI effectiveness.
Lab work
Perform Now Assist Readiness Evaluation
Module 3: Introduction to Now Assist
Objectives
Define Now Assist, its key components, and how it supports enterprise users. You’ll explore the Now Assist foundation and core platform capabilities that power generative AI experiences, understand how Enterprise AI Search enhances discovery, answers, and self-service across ServiceNow workflows, and discover how Now Assist Skills extend the platform with custom generative AI behaviors tailored to your organization. You’ll also see how Now Assist enhances Virtual Agent with conversational intelligence and natural language interactions.
Lab work
Configure Now Assist in Virtual Agent, Leverage Knowledge Graph in Search
Module 4: Model Provider Strategy
Objectives
Explore the ServiceNow model provider strategy and how it supports enterprise AI. Review model deployment options, understand how Now LLMs and integrated providers are used across workflows, and examine how model selection and governance are managed through the AI Control Tower and Now Assist Admin Console. Also discussed are the ServiceNow AI infrastructure and generative AI data flows.
Lab work
Explore Model Selection in the AI Control Tower and the Now Assist Admin Console
Module 5: Now Assist Administration
Objectives
Manage Now Assist solutions across your platform using the Now Assist Admin Console. Configure Now Assist Skills, set up experiences, enable data sharing and language support, explore dashboards to measure usage, adoption, performance, and track subscription management analytics.
Lab work
Now Assist Admin Console Walkthrough, Now Assist Skill Activation, Now Assist Context Menu Configuration
Module 6: AI Governance and Guardrails
Objectives
Configure Now Assist Guardian guardrails for content moderation, understand how content moderation and data masking work together, and set up Now Assist privacy rules in the Admin Console.
Lab work
Configure Content Moderation and Privacy Rules
Module 7: Extending ServiceNow with the Now Assist Skill Kit
Objectives
Create and manage skills using the Now Assist Skill Kit, craft effective prompts to drive AI interactions, augment skills with integrated tools, evaluate skill performance for accuracy and reliability, and publish and activate skills to augment existing and create new workflows leveraging Gen AI functionality.
Lab work
Build, test, evaluate, and deploy custom Now Assist skills in the Now Assist Skill Kit
Module 8: Now Assist Agents
Objectives
Explore the core building blocks of agentic workflows, AI agents, and the tools that power them. Build AI agents that perform reasoning-based tasks within agentic workflows. Navigate the AI Agent Studio to design, configure, and manage agents and workflows, and track agentic usage, outcomes, and overall value.
Lab work
Design and build Agentic Workflows and AI Agents
Module 9: Evaluating Agentic Workflows
Objectives
Select evaluation metrics, such as task completion, performance, and tool execution. Configure evaluation runs to assess the agentic workflow’s quality, performance, and reliability.
Lab work
Assess Agentic Workflow effectiveness
Module 10: AI Agentic Fabric and MCP
Objectives
Define AI Agent Fabric and its benefits, discuss common protocols to enable agentic interoperability, configure ServiceNow AI Agents using the MCP Client Tool, and explore use cases for augmenting AI agents using MCP and A2A.
Lab work
Allow your AI Agent to “talk” to external systems using an MCP tool
Module 11: AI Control Tower
Objectives
Get introduced to the ServiceNow AI Control Tower, a centralized hub for managing AI transformation initiatives across your organization. Learn how to track AI value, adoption, risks, and compliance in alignment with your overall AI strategy. Conclude with a practical use case showcasing collaboration among an AI Steward, Product Owner, and Risk and Compliance Manager to drive coordinated, effective AI adoption.
Lab work
Perform a guided tour exploring dashboards and administrative interfaces
Good to know
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