Overview
This category introduces artificial intelligence as Version 5 treats it. The first topic asks you to define AI, AI maturity, generative AI and agentic AI, and to explain how AI supports the Product and Service Lifecycle, its automation, and value chain activities. The second topic asks you to define AI governance and understand the ITIL AI Capability Model.
Nothing like this existed in ITIL 4 Foundation, which mentioned automation only in general terms. Version 5 calls itself AI-native: AI appears in the four dimensions, in each lifecycle activity and in a separate ITIL AI Governance publication and qualification. At Foundation level the expectation is modest. You need the vocabulary, a sense of where AI helps across discover to support, and an understanding that AI use must be governed. The AI Capability Model sets out six capabilities: creation, curation, clarification, cognition, communication and coordination.
How it's tested
With one likely question, expect a straight definition or a statement to evaluate. The stem may describe an AI tool and ask whether it is generative or agentic, ask what AI governance is for, or ask which statement about AI in the lifecycle is correct.
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Generative or agentic?
A tool that drafts knowledge articles is contrasted with one that resolves tickets by taking actions, and you classify the described tool.
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Purpose of AI governance
Options describe AI governance and you choose the one about directing and controlling AI use, risk and accountability.
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AI in the lifecycle
Statements about AI use are given and you pick the true one: AI can support every lifecycle activity rather than only operate or support.
A stem describes an AI assistant that reads a user's request, checks entitlements, creates the account and closes the ticket without human input, then asks what kind of AI this is. Generative AI tempts because the tool understands language, but its defining trait is taking a sequence of actions to reach a goal on its own. That autonomy makes it agentic AI, which also raises governance questions.
Syllabus topics 2
Official syllabus topics from the PeopleCert outline, in outline order.
6.1 Introduction to AIAI, AI maturity, generative AI and agentic AI, and AI's role in the lifecycle, automation and value chain.
- What it means
- Artificial intelligence is technology that performs tasks normally needing human intelligence, such as understanding language, recognising patterns and making decisions. AI maturity describes how far an organization has progressed in adopting and managing AI. Generative AI creates new content such as text, code or images. Agentic AI acts with some autonomy, planning and executing steps to reach a goal.
- What to understand
- Version 5 presents AI as able to support every lifecycle activity: analysing demand in discover, drafting designs, assisting build and testing, predicting risk in transition, spotting anomalies in operate, personalising deliver, and handling requests in support. AI also extends automation of value chain activities. Understand that the benefit depends on governance and on keeping humans accountable for outcomes, consistent with optimize and automate.
- How it shows up
- Definition matching among AI terms, or a statement about where AI can help in the lifecycle.
- Common confusion
- Treating generative and agentic AI as the same; one creates content, the other acts toward goals.
6.2 ITIL AI GovernanceThe definition of AI governance and the ITIL AI Capability Model.
- What it means
- AI governance is how an organization directs and controls its use of AI so that it creates value while risks, ethics, compliance and accountability are managed. It extends the organization's existing governance rather than replacing it.
- What to understand
- The ITIL AI Capability Model describes six capabilities that AI can provide: creation, curation, clarification, cognition, communication and coordination. Organizations use it to classify AI use cases by the capability involved, judge the risks each brings, and choose suitable controls. At Foundation level, understand what the model is for rather than how to apply its controls in detail.
- How it shows up
- Recognising the purpose of AI governance or the AI Capability Model from a list of statements.
- Common confusion
- Assuming the capability model is a maturity scale; it classifies capabilities, not adoption stages.
High-yield concepts
The terms, rules and formulas this domain turns into questions most often.
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Artificial intelligence
Technology performing tasks that normally require human intelligence.
- Remember
- Broad umbrella term.
- Tested as
- Definition recall.
- Trap
- Equating all AI with chatbots.
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AI maturity
How far an organization has progressed in adopting and managing AI.
- Remember
- A measure of the organization, not the tool.
- Tested as
- Definition recall.
- Trap
- Confusing it with the capability model.
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Generative AI
AI that creates new content such as text, code or images.
- Remember
- Produces outputs; does not act alone.
- Tested as
- Classification of a described tool.
- Trap
- Labelling a tool that executes tasks as generative.
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Agentic AI
AI that plans and takes actions toward a goal with some autonomy.
- Remember
- Autonomy increases governance needs.
- Tested as
- Classification of a described tool.
- Trap
- Assuming it is simply a better chatbot.
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AI across the lifecycle
AI can support each of the eight activities from discover to support.
- Remember
- Not limited to support or operate.
- Tested as
- True statement questions.
- Trap
- Choosing an option that confines AI to the service desk.
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AI governance
Directing and controlling AI use for value, risk, ethics and accountability.
- Remember
- Builds on existing governance.
- Tested as
- Purpose questions.
- Trap
- Treating it as a purely technical control.
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ITIL AI Capability Model
Six capabilities: creation, curation, clarification, cognition, communication, coordination.
- Remember
- Used to classify use cases and match controls.
- Tested as
- Recognition of the model's purpose.
- Trap
- Reading it as a five-level maturity model.
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Human accountability
People stay accountable for AI-supported outcomes.
- Remember
- Consistent with optimize and automate.
- Tested as
- Statements about appropriate AI use.
- Trap
- Choosing full automation without oversight as best practice.
Side by side
Concepts candidates mix up, compared on the point that decides the answer.
Types of AI in the syllabus
| Concept | Meaning | Key difference | Common trap |
|---|---|---|---|
| AI | Machines performing tasks that need human-like intelligence | The umbrella term | Using it as a synonym for generative AI |
| Generative AI | Creates new content | Output is content | Assigning it autonomous actions |
| Agentic AI | Plans and acts toward goals | Output is action | Ignoring its higher governance needs |
Governance terms
| Concept | Meaning | Key difference | Common trap |
|---|---|---|---|
| Governance | How an organization is directed and controlled | Applies to everything | Thinking AI needs a separate system |
| AI governance | Direction and control of AI use | Extends governance to AI risks and ethics | Treating it as only a technical policy |
| AI Capability Model | Six capabilities AI can provide | Classifies use cases for control | Confusing it with AI maturity |
Exam traps
Each trap is an answer that looks right. Learn the clue that should change your mind.
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Language means generative
- What candidates pick
- Generative AI for any tool that understands requests in natural language.
- Why it looks right
- Language models are the best-known AI.
- Why it's wrong
- If the tool takes actions toward a goal on its own, it is agentic, whatever interface it uses.
Clue to watch for Verbs like executes, resolves, closes or provisions.
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AI only at the service desk
- What candidates pick
- A statement that AI mainly helps support.
- Why it looks right
- Chatbots are the most visible use.
- Why it's wrong
- Version 5 describes AI supporting every lifecycle activity from discover to support.
Clue to watch for Options with only or mainly.
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Remove humans
- What candidates pick
- Full automation without oversight as the ideal.
- Why it looks right
- It promises speed and cost savings.
- Why it's wrong
- Version 5 keeps people accountable and requires governance of AI use.
Clue to watch for Statements about best or recommended practice.
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Capability equals maturity
- What candidates pick
- The AI Capability Model described as stages of adoption.
- Why it looks right
- Many models are maturity ladders.
- Why it's wrong
- The model lists six capabilities AI provides; AI maturity is a separate concept.
Clue to watch for The stem names capabilities or use cases.
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AI governance as IT policy
- What candidates pick
- AI governance defined as access controls on AI tools.
- Why it looks right
- Controls are part of governance.
- Why it's wrong
- AI governance covers direction, value, risk, ethics and accountability, not only technical restrictions.
Clue to watch for Words like direct, control or accountability.
Answer framework
Use this short check for the single question this category is likely to produce.
- Decide whether the stem asks for an AI type, AI's role in the lifecycle, or AI governance and its capability model.
- For type questions, ask whether the tool produces content, which is generative, or takes actions toward a goal, which is agentic.
- For lifecycle questions, prefer statements saying AI can support any of the eight activities, and reject options that confine it to one area.
- For governance questions, choose options about directing and controlling AI use with accountability, value and risk in view, rather than narrow technical controls.
- If the capability model appears, remember it lists six capabilities used to classify use cases; it is not a maturity ladder or a set of lifecycle stages.
Practice question
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Study strategy
Allow one focused hour. Begin by writing the four definitions from the first topic in your own words and adding a workplace example for each, such as a summarising assistant for generative AI and a ticket-resolving agent for agentic AI.
Then walk through the eight lifecycle activities and note one realistic AI use for each. This reinforces the lifecycle category at the same time and prepares you for statements claiming AI belongs only in one place. Finish with governance: learn the definition, the six capabilities as a list, and the purpose of the model in one sentence.
Do not go deeper into machine learning techniques, model types or regulation; they are outside this syllabus. Instead, test yourself with two or three practice questions and confirm you can explain each wrong option. If you plan to continue to the ITIL AI Governance module, keep your notes, since that module expands the capability model and its controls in detail.
FAQ
How many questions come from ITIL and AI?
ITIL and AI is weighted at 2.5% of the Version 5 exam, which suggests about one of 40 questions. The weighting comes from PeopleCert; the count is our estimate.
Was AI part of ITIL 4 Foundation?
Not as a topic. ITIL 4 Foundation discussed automation in general terms. Version 5 adds AI definitions, AI governance and the AI Capability Model to the Foundation syllabus.
What is the difference between generative and agentic AI?
Generative AI creates content such as text or code. Agentic AI plans and takes actions toward a goal with some autonomy, such as resolving a request end to end.
What are the six AI capabilities?
The ITIL AI Capability Model lists creation, curation, clarification, cognition, communication and coordination. Organizations use them to classify AI use cases and choose controls.
Do I need technical AI knowledge?
No. The syllabus tests vocabulary and concepts at Bloom's levels 1 and 2. Knowledge of algorithms or model training is not required.
Is there a separate ITIL AI qualification?
Yes. Version 5 includes an ITIL AI Governance publication and module beyond Foundation, which covers the capability model and AI controls in depth.
Other Enterprise Architecture & IT Governance certifications
Where the same subject shows up in other exams. Cards marked "Same subject" open the matching domain.
Test your Domain 6 knowledge
Check that you can tell generative from agentic AI, define AI governance and recall the six AI capabilities in a short practice set.
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