Free AB-731 practice test: 20 questions
Twenty questions across the three AB-731 skill areas, weighted roughly as the real exam is: seven on business value, eight on Microsoft AI apps and services, and five on implementation and adoption. These are original scenario questions. Read the business need and the constraint before choosing the tool or action, and give yourself about 10 minutes.
Identify the business value of generative AI solutions
Question 1. A manager asks a generative AI assistant: Write something about our new product. The output is generic. Without changing the model or the data, what change would most improve the result?
- A. Add context to the prompt: audience, tone, key features and the desired format
- B. Wait for a newer version of the model
- C. Make the request shorter
- D. Repeat the same request until a better answer appears
Show answer
Answer: A
Prompt engineering improves results by supplying context, a role, the audience, the desired format and constraints, so the model has what it needs. Waiting for a new model release changes nothing now. Shortening the request removes context and usually makes output more generic. Asking the same vague request repeatedly gives variations of the same generic answer.
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Question 2. A team sends a 60-page report and asks for a one-paragraph summary many times per day. Costs are rising. Which action reduces token usage the most without losing the purpose?
- A. Ask the model for a much longer summary each time
- B. Give the tool to more users so costs are shared
- C. Send only the relevant sections, or summarise once and reuse the result
- D. Remove the instructions from the prompt but keep the full report
Show answer
Answer: C
Retrieving only the relevant sections, or summarising once and reusing the result, cuts the input tokens sent on each call, which are the main cost driver here. Asking for a longer summary increases output tokens. Adding more users raises total usage. Removing the instruction text barely changes the 60-page input and makes output worse.
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Question 3. A bank builds a loan-assistant model using only the records of customers from one city. After launch, it performs poorly for customers from other regions. Which data principle was violated?
- A. The data was not encrypted at rest
- B. There was too much data
- C. The prompts were too long
- D. The dataset was not representative of the customers served
Show answer
Answer: D
The training data was not representative of the people the system serves, so quality varies by group. Encryption protects confidentiality but does not make a dataset representative. Having a lot of data is irrelevant if it comes from one narrow slice. Prompt length is unrelated to training data coverage.
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Question 4. A retailer wants to predict next month's demand for each product from three years of sales history. Which type of AI fits this task best?
- A. A generative model that writes marketing text
- B. A machine learning model trained on the sales history
- C. An image generation model
- D. A chatbot that has no access to the sales data
Show answer
Answer: B
Forecasting numeric outcomes from historical patterns is a classic machine learning (predictive) task. A text-generating model is built to produce content, not to deliver reliable numeric forecasts. Image generation creates pictures and does not forecast sales. A chatbot without data cannot predict anything from history.
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Question 5. Employees have started pasting confidential customer data into an unapproved public AI website. What is the most appropriate leadership response?
- A. Provide an approved AI tool and publish a clear usage policy with training
- B. Ignore it because the data is only text
- C. Ban every AI tool without offering an alternative
- D. Email staff to be careful but change nothing else
Show answer
Answer: A
Providing an approved AI tool with appropriate data protection, backed by a clear usage policy and training, removes the reason for the workaround and addresses the data security risk. Ignoring it leaves customer data exposed. Banning every AI tool pushes the behaviour out of sight and forfeits the value. Asking staff to be careful without any alternative or policy is not a control.
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Question 6. A machine learning model that predicts customer churn was accurate at launch, but its accuracy has dropped over a year because customer behaviour has changed. Which part of the machine learning lifecycle was missing?
- A. Collecting data for the first time
- B. Writing a more detailed prompt
- C. Monitoring performance and retraining with new data
- D. Buying additional licences
Show answer
Answer: C
Deployed models need ongoing monitoring, and retraining on fresh data when performance drifts. Initial data collection was done at launch and does not address drift. Writing a better prompt is a generative AI concern and not how a trained predictive model is fixed. Buying more licences has no effect on accuracy.
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Question 7. A legal team uses generative AI to draft contract clauses. One draft cites a court case that does not exist. What should leadership require going forward?
- A. Limit the tool to very short outputs
- B. Trust output that is fluent and well formatted
- C. Remove human review to save time
- D. Require human verification of facts and citations, and ground the tool on trusted sources
Show answer
Answer: D
Generative AI can produce fabrications that sound plausible. Human review of citations and facts, plus grounding on trusted sources, is the right control for high-stakes content. Using the tool only for short text does not stop invented facts. Trusting output because it is well written is the exact risk. Removing all review to save time makes the problem worse.
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Identify benefits, capabilities, and opportunities for Microsoft’s AI apps and services
Question 8. Employees without a Microsoft 365 Copilot add-on licence want a secure AI chat for general questions and web-based research, signed in with their work account. Which experience matches?
- A. Copilot Studio
- B. Microsoft 365 Copilot Chat
- C. Azure Vision in Foundry Tools
- D. A personal consumer account on a public chatbot
Show answer
Answer: B
Microsoft 365 Copilot Chat is the chat experience for signed-in work accounts on web and mobile, available without the full Copilot add-on. Copilot Studio is for building agents. Azure Vision in Foundry Tools analyses images and is not a chat assistant for staff. A personal consumer account is not the work-account, protected route the scenario asks for.
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Question 9. A sales manager wants to turn a Word proposal into a draft slide deck and then analyse a table in Excel, without leaving the apps she is working in. Which capability serves this?
- A. Azure AI Search
- B. A custom model trained in Microsoft Foundry
- C. Copilot in the Microsoft 365 apps
- D. Copilot Studio
Show answer
Answer: C
Copilot in the Microsoft 365 apps works inside Word, PowerPoint and Excel, so she can draft a deck from a document and analyse data in place. Azure AI Search indexes content for applications and is not an in-app assistant. A custom model needs development. Copilot Studio builds agents rather than assisting directly in the document.
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Question 10. The HR team wants a no-code agent that answers benefits questions from approved HR documents and can be published to employees. Which product fits best?
- A. Microsoft Copilot Studio
- B. Azure Vision in Foundry Tools
- C. A model trained from scratch by developers
- D. Analyst in Microsoft 365 Copilot
Show answer
Answer: A
Microsoft Copilot Studio lets business users build and publish agents with low-code or no-code tools, grounded on approved knowledge sources. Azure Vision in Foundry Tools handles image analysis. Building a model from scratch is slow and unnecessary. Analyst in Copilot analyses data for a user and is not a tool for publishing a benefits agent.
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Question 11. A director asks why Microsoft 365 Copilot can answer questions about her recent meetings and documents but not about a colleague's private files. Which capability makes this possible?
- A. Token-based billing
- B. A fine-tuned model for each employee
- C. Azure Vision in Foundry Tools
- D. Microsoft Graph grounding that respects the user’s permissions
Show answer
Answer: D
Microsoft Graph connects Copilot to the user’s work data, such as mail, calendar, meetings and files, and access follows the permissions of the signed-in user. Token billing is about cost, not access. Fine-tuning bakes behaviour into a model and does not grant per-user access. Image analysis has nothing to do with meetings or documents.
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Question 12. An analyst uploads several quarterly sales spreadsheets and wants Copilot to work through them step by step, find trends and produce charts. Which Copilot agent is the best fit?
- A. Researcher
- B. Analyst
- C. Copilot Studio
- D. Azure AI Search
Show answer
Answer: B
Analyst is designed for data analysis, reasoning through files and producing insights and charts. Researcher is for multi-source research reports across work and web content. Copilot Studio builds agents. Azure AI Search retrieves indexed content for applications and does not analyse spreadsheets for a user.
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Question 13. A support centre needs to classify millions of short tickets per month at the lowest cost and with fast responses. Accuracy needs are moderate. How should the team choose a model?
- A. Always choose the largest and newest model available
- B. Choose by whichever model has the most familiar brand name
- C. Pick a smaller, lower-cost model whose accuracy meets the need
- D. Classify all tickets manually
Show answer
Answer: C
Matching the model to the need means weighing capability against cost and latency. For simple, high-volume classification, a smaller and cheaper model is usually the better fit. The largest model costs more and is slower than needed. Choosing by brand name ignores the requirements. Rejecting all models and doing it manually forfeits the automation benefit.
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Question 14. A company wants to build its own knowledge assistant over thousands of internal documents so that answers are retrieved from them. Which Foundry Tools capability provides the search layer?
- A. Azure AI Search
- B. Azure Vision in Foundry Tools
- C. Researcher in Microsoft 365 Copilot
- D. A shared spreadsheet of document titles
Show answer
Answer: A
Azure AI Search indexes documents and retrieves relevant content for grounding, which is the search layer of a RAG solution. Azure Vision in Foundry Tools analyses images. Researcher is a Copilot agent for users and not a component you build into your own application. A spreadsheet is not a search service for thousands of documents.
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Question 15. The CIO compares an integrated Microsoft AI solution with several unconnected AI tools from different vendors. Which benefit most supports the integrated choice from a risk perspective?
- A. It has fewer buttons in the interface
- B. It is more popular in advertising
- C. It guarantees that responses never contain errors
- D. Existing identity, security and compliance controls apply consistently
Show answer
Answer: D
An integrated solution lets identity, security, compliance and safety controls apply consistently across the AI experience, which reduces risk. A smaller number of buttons is a usability point. Marketing popularity is not a risk control. A guarantee of never having errors does not exist for generative AI.
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Identify an implementation and adoption strategy for Microsoft’s AI apps and services
Question 16. An AI screening tool used in recruitment rejects a much higher share of applicants from one demographic group, with no job-related reason. Which responsible AI principle is most directly affected?
- A. Transparency
- B. Fairness
- C. Inclusiveness
- D. Privacy
Show answer
Answer: B
Fairness means AI systems should treat people equitably and avoid disadvantaging groups. Transparency is about explaining how systems work and when AI is used. Inclusiveness is about designing for a range of abilities and backgrounds; it is related but fairness is the principle about unequal outcomes. Privacy concerns how personal data is handled, which is not the described problem.
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Question 17. Before a company-wide rollout, executives want a cross-functional group to set AI strategy, oversight and policies, and to align legal, security, HR and business units. What should they establish?
- A. An AI council
- B. One developer who decides alone
- C. The vendor’s sales team
- D. A mailing list for end users
Show answer
Answer: A
An AI council brings the functions together to guide strategy, oversight and alignment. A single developer cannot represent legal, security and HR. A vendor sales team has its own interest. An end-user mailing list shares news but sets no policy.
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Question 18. In a survey, employees say they do not trust AI results and fear it will replace them. Which response best addresses this barrier to adoption?
- A. Mandate use with no explanation
- B. Keep the rollout plan private
- C. Communicate the purpose openly and provide role-based training
- D. Reduce the training budget
Show answer
Answer: C
Open communication about purpose, role-based training and visible leadership support address fear and mistrust, which are common human barriers. Mandating use without explanation increases resistance. Hiding the rollout plan raises suspicion. Cutting training budgets makes the skills gap and distrust worse.
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Question 19. A company is about to roll out Copilot to 5,000 staff. Who should the AI adoption team include so that rollout, training, measurement and risk are all covered?
- A. Only members of the IT help desk
- B. Only senior executives
- C. Only temporary vendor staff
- D. A cross-functional group from business, IT, security and people or learning teams
Show answer
Answer: D
A cross-functional team that includes business owners, IT, security, HR or learning and communications covers the full set of rollout needs. An IT-only team misses business use cases and change management. Executives alone are too far from daily work. Temporary vendor staff will leave and do not own the outcome.
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Question 20. A business plans a steady, high, predictable monthly volume of requests to Foundry Tools and wants to lower the unit cost. Which subscription approach should it consider?
- A. Stay on pay-as-you-go only, whatever the volume
- B. Evaluate a commitment tier
- C. Rely on free trials permanently
- D. Avoid estimating the usage
Show answer
Answer: B
Commitment tiers suit predictable, high usage by trading a commitment for a lower unit cost. Pay-as-you-go is flexible and better for variable or low usage. Using only free trials is not a production approach. Refusing to estimate usage makes cost control impossible.
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