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Free Scrum Master AI Essentials (PSM-AI Essentials) Practice Assessment

Free Scrum Master AI Essentials (PSM-AI Essentials) Practice Assessment

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This is a good sign that you are ready to attempt the Professional Scrum Master – AI Essentials (PSM-AI Essentials) assessment from Scrum.org.

Click ‘View questions’ below to see which you got right and wrong and review the feedback for each question. You can retake the assessment if you wish.

Do you want more practice questions? Try our Ultimate Scrum Master AI Essentials (PSM-AI Essentials) Practice Assessment.

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Question 1 of 20

1. Question

Why should conversational AI tools not be treated as authorities?

They can produce incorrect outputs
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They refuse to provide references and citations
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They cannot generate drafts
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They are always outdated
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Question 2 of 20

2. Question

Why can algorithmic bias occur in AI systems?

Models learn from historical data that may be incomplete or skewed
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Models intentionally discriminate between users
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Bias only appears during deployment
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Bias is caused by too much data that cannot be effectively processed
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Question 3 of 20

3. Question

How should Developers treat AI-generated code suggestions?

As input from a fast but occasionally wrong junior pair
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As production-ready and trustworthy by default
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As a replacement for human code reviews
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As authoritative design decisions
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Question 4 of 20

4. Question

What is the recommended use of AI in forecasting and planning?

Producing ranges based on historical data
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Guaranteeing delivery timelines and reliable project plans
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Removing the need for capacity discussions within the Scrum Team
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Fixing scope commitments
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Question 5 of 20

5. Question

How should AI be positioned within a Scrum Team?

As a tool that reduces uncertainty while people retain judgement
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As a replacement for team decision making
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As the primary driver of delivery
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As an authority on priorities and scope
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Question 6 of 20

6. Question

Why is safe data handling critical when using AI in organisations?

AI gains depend on secure access, controls, and consent
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It improves AI creativity
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It increases model accuracy automatically
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It removes the need for reviews
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Question 7 of 20

7. Question

How can AI assist with Product Backlog management?

By finding duplicates
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By deciding backlog order
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By accepting delivery risk
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By approving scope changes
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Question 8 of 20

8. Question

What is the primary purpose of a clear Definition of Done?

To turn vague expectations into measurable quality
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To replace the need for acceptance criteria for each Product Backlog item
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To speed up estimation, forecasting and planning
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To document architecture decisions
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Question 9 of 20

9. Question

What responsibility does the Scrum Master retain when using AI for brainstorming?

Steering facilitation and protecting team ownership of decisions
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Approving all AI generated ideas
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Writing Product Backlog Items independently to reduce refinement effort
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Estimating effort on behalf of the team
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Question 10 of 20

10. Question

What is one of the most practical uses of AI in teaching?

Creating educational videos at scale
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Replacing human educators entirely
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Assessing learner performance automatically
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Designing physical classrooms
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Question 11 of 20

11. Question

Why does context engineering reduce the need for repeated clarification?

The AI can respond based on an ongoing situation
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The AI no longer makes assumptions when responding
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The AI becomes fully autonomous
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Users no longer need to review outputs
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Question 12 of 20

12. Question

What factor most strongly influences the quality of ChatGPT’s output?

How clearly and precisely the user describes their request
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The length of the conversation
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The time of day it is used
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Whether the user understands programming languages
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Question 13 of 20

13. Question

What is the recommended way to treat outputs from generative AI?

As drafts requiring human review
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As final answers suitable for direct publication
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As objective facts without verification
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As secure and unbiased by default
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Question 14 of 20

14. Question

What is the purpose of the pretraining phase in model development?

Teaching general language and domain patterns
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Enforcing safety rules and tone
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Reducing the size of the model for efficiency
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Limiting creative outputs
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Question 15 of 20

15. Question

What defines the current phase of modern AI?

Large scale models trained on vast data and widely deployed
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Exclusive use in specialist research laboratories and scientific domains
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Reliance on hand-coded rules defined by humans
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Limited interaction with users
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Question 16 of 20

16. Question

What was a key limitation of early rule based AI systems?

They struggled with complexity and ambiguity
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They required too much training data to be useful
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They could not follow explicit instructions from users
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They lacked mathematical foundations
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Question 17 of 20

17. Question

Why is human review still essential when using Generative AI in Scrum Teams?

Outputs may be biased or incorrect
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AI tools cannot generate Scrum-related content
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AI systems always expose sensitive data
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AI cannot follow prompt instructions
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Question 18 of 20

18. Question

Which option correctly describes Machine Learning?

A subset of AI where models learn patterns from data
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A rule-writing technique used by developers
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A synonym for Neural Networks
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A method limited to image processing
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Question 19 of 20

19. Question

What best describes Artificial Intelligence?

Systems that perform tasks linked to human judgement
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Software that always replaces human decision making
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Tools that only follow fixed, pre-written rules
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Algorithms limited to numerical calculations only
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Question 20 of 20

20. Question

How can AI assist during or after live facilitation?

By summarising outputs and identifying themes
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By leading the discussion and ensuring consensus
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By resolving team conflicts automatically
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By making binding decisions
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