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AB-620 practice questions

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Question 1Plan and design AI solutions

An organization wants a solution that automatically extracts structured fields from scanned invoices. Which Azure AI service is purpose-built for this scenario?

  1. Azure AI Language
  2. Azure AI Vision
  3. Azure AI Speech
  4. Azure AI Document Intelligence Correct answer.

Explanation

Document Intelligence provides prebuilt and custom models that extract fields, tables, and key-value pairs from documents such as invoices and receipts. Vision handles image analysis, Language handles text analytics, and Speech handles audio.

Question 2Plan and design AI solutions

A team needs a retrieval-augmented generation pattern where the model answers questions using their own documents. Which design best supports this requirement?

  1. Store documents in a search index and ground responses with retrieved passages Correct answer.
  2. Fine-tune a base model on the full document set for every update
  3. Enable content filtering to inject document text into prompts
  4. Increase the model temperature so it can recall more content

Explanation

RAG grounds model output by retrieving relevant passages from an indexed knowledge source and adding them to the prompt. This keeps answers current without retraining and reduces hallucination.

Question 3Plan and design AI solutions

Which Azure OpenAI capability allows a model to call external functions or APIs based on user intent?

  1. Provisioned throughput
  2. Function calling Correct answer.
  3. Embeddings
  4. Content filtering

Explanation

Function calling lets the model emit structured arguments that your application uses to invoke external tools or APIs. Embeddings produce vectors, filtering screens content, and provisioned throughput is a capacity model.

Question 4Plan and design AI solutions

A solution must keep all prompt and response data within a specific geographic region for compliance. Which design decision most directly satisfies this requirement?

  1. Deploy resources in a region that meets the residency requirement Correct answer.
  2. Enable diagnostic logging to a global workspace
  3. Set the model temperature to zero
  4. Use a larger model tier

Explanation

Data residency is controlled by the region in which the Azure resources are deployed. Model parameters and tiers do not affect where data is processed, and global logging can conflict with residency goals.

Question 5Plan and design AI solutions

When designing a solution that uses Azure OpenAI, which factor most influences whether to use the pay-as-you-go model versus provisioned throughput?

  1. The number of prompt templates stored
  2. The programming language used by the client
  3. The number of developers on the team
  4. The predictability and volume of token consumption Correct answer.

Explanation

Provisioned throughput is cost-effective for steady, high-volume workloads, while pay-as-you-go suits variable or low usage. Consumption patterns are the primary driver of this choice.

Question 6Plan and design AI solutions

Which Azure AI service should be used to build a conversational agent that answers FAQ questions from a knowledge base with minimal custom code?

  1. Azure AI Search with semantic ranking only
  2. Azure AI Bot Service with a language understanding model Correct answer.
  3. Azure AI Translator
  4. Azure AI Content Safety

Explanation

Azure AI Bot Service combined with language understanding supports building conversational agents that resolve intents and answer from knowledge sources. The other services provide search, moderation, or translation rather than conversational orchestration.

Question 7Plan and design AI solutions

A design requires that user prompts never be used to improve the underlying foundation model. Which approach addresses this concern?

  1. Disable content filtering
  2. Rely on the default model behavior without configuration
  3. Use an Azure OpenAI deployment where data is not used for model training Correct answer.
  4. Store prompts in a public storage account

Explanation

Azure OpenAI deployments do not use customer prompts or completions to train or improve foundation models. Public storage and disabling filtering do not address training data concerns.

Question 8Plan and design AI solutions

Which design pattern best reduces hallucination when an AI solution must answer questions about a regulated policy corpus?

  1. Use the smallest available model to reduce cost
  2. Raise the temperature to encourage varied answers
  3. Shorten the system prompt to save tokens
  4. Ground responses in retrieved source passages and require citations Correct answer.

Explanation

Grounding answers in retrieved passages and requiring citations ties output to verifiable sources and reduces fabrication. Higher temperature and smaller models can increase inaccuracy, and prompt length is not the cause of hallucination.

Question 9Plan and design AI solutions

A solution must classify incoming support tickets into categories and route them. Which combination of Azure AI services fits best?

  1. Azure AI Content Safety and Azure AI Search
  2. Azure AI Language custom text classification and an orchestration layer Correct answer.
  3. Azure AI Speech and Azure AI Translator
  4. Azure AI Vision and Azure AI Document Intelligence

Explanation

Custom text classification in Azure AI Language assigns categories to text, and an orchestration layer routes based on the result. The other combinations address unrelated modalities or functions.

Question 10Plan and design AI solutions

Which statement best describes the role of embeddings in a semantic search design?

  1. They enforce rate limits on API calls
  2. They represent text as vectors so similarity can be computed Correct answer.
  3. They translate queries into multiple languages
  4. They compress documents to reduce storage cost

Explanation

Embeddings map text into a vector space where semantically similar content is close together, enabling similarity search. They are not a compression, translation, or throttling mechanism.

Question 11Plan and design AI solutions

A team is designing a multi-stage pipeline that ingests documents, extracts text, chunks it, generates embeddings, and indexes it. Where should chunking occur?

  1. After indexing in the search service
  2. Only at query time
  3. Before text extraction
  4. After text extraction and before embedding generation Correct answer.

Explanation

Chunking happens after text is extracted and before embeddings are generated so each chunk can be embedded and indexed. Indexing and query time occur downstream of embedding.

Question 12Plan and design AI solutions

Which Azure feature helps protect an AI application from prompt injection attacks?

  1. Azure Monitor metrics
  2. Azure AI Translator
  3. Prompt Shields in Azure AI Content Safety Correct answer.
  4. Azure Key Vault

Explanation

Prompt Shields detect and block attempts to manipulate a model through injected instructions. Translator, metrics, and Key Vault serve unrelated purposes.

Question 13Plan and design AI solutions

A design requires that only authorized employees can query an internal AI assistant, and access must be auditable. Which approach best meets this?

  1. Disable logging to reduce storage costs
  2. Authenticate users with Microsoft Entra ID and log access Correct answer.
  3. Rely on network isolation alone
  4. Embed a shared API key in the client application

Explanation

Identity-based authentication with Entra ID enforces per-user authorization, and logging provides an audit trail. Shared keys and network isolation alone do not identify individual users, and disabling logging removes auditability.

Question 14Plan and design AI solutions

Which scenario is the strongest candidate for fine-tuning rather than retrieval augmentation?

  1. Answering questions over a knowledge base that changes weekly
  2. Enforcing data residency requirements
  3. Teaching a consistent output style and format for a fixed task Correct answer.
  4. Looking up the current status of a support ticket

Explanation

Fine-tuning adapts model behavior, tone, and format for a stable task. Rapidly changing knowledge is better served by retrieval, live lookups require tool calls, and residency is a deployment concern.

Question 15Plan and design AI solutions

An AI solution must process both text and images in a single request. Which model capability should be selected?

  1. A speech-to-text model
  2. A text-only completion model
  3. A multimodal model Correct answer.
  4. An embeddings-only model

Explanation

Multimodal models accept more than one input modality, such as text and images, in a single request. Text-only, embeddings-only, and speech models each handle a narrower input type.

Question 16Plan and design AI solutions

A design must limit the blast radius of a compromised API key used by an AI application. Which practice best achieves this?

  1. Share the key across all environments
  2. Store the key in source code for reliability
  3. Use managed identity and rotate secrets stored in Key Vault Correct answer.
  4. Give the key full subscription-level permissions

Explanation

Managed identities remove embedded secrets, and rotating secrets in Key Vault limits exposure if a key is compromised. Hardcoding, over-privileging, and sharing keys widen the blast radius.

Question 17Plan and design AI solutions

Which design consideration is most important when choosing a chunk size for a retrieval index?

  1. Balancing context completeness against retrieval precision Correct answer.
  2. Maximizing the number of chunks regardless of content
  3. Ensuring chunks are always a single word
  4. Setting chunk size equal to the model's maximum token limit

Explanation

Chunk size trades off completeness of context against precision of retrieval; chunks that are too large dilute relevance and too small lose context. Maximizing count or using extreme sizes harms quality.

Question 18Plan and design AI solutions

A solution must moderate user-generated text for hate, violence, and self-harm before display. Which service should be integrated?

  1. Azure AI Content Safety Correct answer.
  2. Azure AI Speech
  3. Azure AI Translator
  4. Azure AI Document Intelligence

Explanation

Azure AI Content Safety classifies harmful text and imagery across categories such as hate, violence, and self-harm. The other services handle documents, speech, and translation.

Question 19Plan and design AI solutions

An organization wants to deploy an AI assistant that must remain functional if a single Azure region experiences an outage. Which design element addresses this?

  1. Deploy resources across multiple regions with failover Correct answer.
  2. Increase the model temperature
  3. Reduce the token limit per request
  4. Deploy all resources to one region with a single replica

Explanation

Multi-region deployment with failover provides resilience against regional outages. Single-region, single-replica designs have a single point of failure, and model parameters do not affect availability.

Question 20Plan and design AI solutions

Which metric is most useful for evaluating whether a retrieval-augmented solution returns relevant context before generation?

  1. Model temperature setting
  2. Token count of the final answer
  3. Number of API deployments
  4. Recall of relevant passages in the retrieved set Correct answer.

Explanation

Retrieval quality is measured by how many relevant passages appear in the retrieved set, commonly recall or precision at k. Answer length, temperature, and deployment count do not measure retrieval quality.

Question 21Plan and design AI solutions

A design requires processing large volumes of documents asynchronously without blocking user requests. Which approach fits best?

  1. Queue-based background processing with a document pipeline Correct answer.
  2. Synchronous calls inside the user request
  3. Disabling retries to speed up processing
  4. Manual processing by administrators

Explanation

Queue-based background processing decouples long-running document work from user requests and supports scaling. Synchronous in-request processing increases latency, and removing retries reduces reliability.

Question 22Plan and design AI solutions

Which statement best explains why a system prompt should be designed to resist instruction override?

  1. System prompts reduce token costs
  2. System prompts replace the need for content filtering
  3. System prompts establish behavior that user input should not be able to replace Correct answer.
  4. System prompts are visible to all users by default

Explanation

System prompts set the model's role and constraints, and robust design helps prevent user input from overriding those constraints. They are not a cost tool or a substitute for content filtering.

Question 23Plan and design AI solutions

A team wants to compare model outputs against a human-labeled dataset to measure answer quality. Which practice should they adopt?

  1. Increase temperature until outputs look correct
  2. Define evaluation metrics and run a repeatable test set Correct answer.
  3. Skip evaluation if the model is popular
  4. Rely on a single anecdotal example

Explanation

Repeatable evaluation against a labeled test set with defined metrics gives objective quality measures. Anecdotes, tuning until outputs look right, and popularity are not valid evaluation methods.

Question 24Plan and design AI solutions

An AI solution must ensure that responses cite only documents the requesting user is permitted to see. Which design element is essential?

  1. Caching all documents in a shared index without filters
  2. Applying user-specific access filters during retrieval Correct answer.
  3. Using a larger embedding dimension
  4. Increasing the model's context window

Explanation

Access control must be enforced at retrieval time with user-specific filters so the model only receives authorized content. Context size, unfiltered shared indexes, and embedding dimensions do not enforce permissions.

Question 25Plan and design AI solutions

Which Azure service is best suited to convert recorded call audio into searchable text for later analysis?

  1. Azure AI Document Intelligence
  2. Azure AI Speech Correct answer.
  3. Azure AI Vision
  4. Azure AI Content Safety

Explanation

Azure AI Speech provides speech-to-text transcription for audio, enabling downstream search and analysis. The other services process images, moderate content, or extract document fields.

Question 26Plan and design AI solutions

A company wants to build a solution that summarizes long contracts and must decide between a single large prompt and a map-reduce approach. Which factor most directly justifies choosing the map-reduce pattern?

  1. The documents exceed the model's maximum context window. Correct answer.
  2. The documents must be stored in a relational database.
  3. The documents contain scanned images.
  4. The summaries must be translated into several languages.

Explanation

Map-reduce splits a document into chunks that are summarized separately and then combined, which is necessary when the input cannot fit within the model's context window. The other factors relate to OCR, localization, or storage and do not determine the summarization pattern.

Question 27Plan and design AI solutions

A design must ensure that an AI assistant's responses are grounded in the organization's internal product documentation rather than general model knowledge. Which architectural component is essential?

  1. A content safety filter applied to outputs
  2. A larger model with more parameters
  3. A retrieval step that supplies relevant document excerpts to the model Correct answer.
  4. A caching layer in front of the model endpoint

Explanation

Grounding requires that relevant source material be retrieved and included in the model input so answers are based on that material. Model size, output filtering, and caching do not connect responses to the internal corpus.

Question 28Plan and design AI solutions

A team is planning an AI solution and wants to estimate the cost of model usage before launch. Which quantity should they forecast to predict token-based charges?

  1. The number of user accounts in the directory
  2. The number of virtual machines in the subnet
  3. The number of input and output tokens per request multiplied by expected request volume Correct answer.
  4. The number of storage accounts provisioned

Explanation

Token-based pricing depends on how many prompt and completion tokens are processed, so forecasting both per request and multiplying by volume estimates cost. Storage, identities, and compute hosts are unrelated to token consumption.

Question 29Plan and design AI solutions

A solution must let users ask questions over a knowledge base and receive answers that include links to the source passages. Which design element directly enables the citations?

  1. Storing chunk identifiers and source metadata alongside each embedded chunk Correct answer.
  2. Enabling streaming of the response to the client
  3. Increasing the model temperature setting
  4. Compressing the index with a smaller embedding dimension

Explanation

Citations require that each retrieved chunk retain metadata identifying its source so the response can reference it. Temperature, embedding dimension, and streaming affect generation behavior or performance but not traceability to sources.

Question 30Plan and design AI solutions

An organization needs an AI solution that automatically detects the language of incoming messages and translates them into a single working language before analysis. Which design choice is most appropriate?

  1. Restrict input to a single language at the client
  2. Use a language detection step, then a translation service, before the analysis stage Correct answer.
  3. Store all messages untranslated and translate only when a user asks
  4. Rely on the analysis model to interpret every language without preprocessing

Explanation

Explicit detection followed by translation normalizes input so downstream analysis operates on one language consistently. Skipping preprocessing, deferring translation, or restricting input does not meet the requirement to handle multiple languages automatically.

Question 31Plan and design AI solutions

A design review asks why an AI solution should log the model version, prompt template version, and retrieval configuration for each request. Which goal does this logging primarily serve?

  1. Load balancing across regions
  2. Reproducibility and root-cause analysis of response changes over time Correct answer.
  3. Encryption of data at rest
  4. Reduction of token costs per request

Explanation

Recording the model, prompt, and retrieval settings lets teams reproduce and diagnose why outputs changed after a configuration update. These logs do not reduce token usage, encrypt data, or distribute traffic.

Question 32Plan and design AI solutions

An AI solution must enforce that responses never contain personal data such as account numbers, even if such data appears in retrieved documents. Which design approach best meets this requirement?

  1. Apply a redaction step to retrieved content and to generated output before display Correct answer.
  2. Lower the number of retrieved chunks to one
  3. Store the index in a different region
  4. Increase the model's context window

Explanation

Redacting sensitive patterns in retrieved content and again on output provides defense in depth so personal data does not reach the user. Context size, region, and chunk count do not address redaction.

Question 33Plan and design AI solutions

A team is deciding whether to use a prebuilt model or train a custom model for image classification of product defects. Which consideration is most relevant to the decision?

  1. Whether the defect categories are specific to the business and not covered by general models Correct answer.
  2. Whether the images will be stored in blob storage
  3. Whether the development team prefers Python or C#
  4. Whether the solution will be billed monthly or annually

Explanation

Custom training is justified when categories are domain-specific and not reliably recognized by general-purpose models. Billing cadence, programming language, and storage choice do not determine whether a prebuilt model is sufficient.

Question 34Plan and design AI solutions

A solution must route high-confidence automated decisions directly and send low-confidence cases to a human reviewer. Which design element is required to implement this?

  1. A single shared API key for all reviewers
  2. A confidence threshold evaluated per response with a fallback path to human review Correct answer.
  3. A nightly batch job that reprocesses all records
  4. A fixed temperature of zero for all requests

Explanation

A threshold on the model's confidence score determines whether a case is auto-approved or escalated. Temperature, key management, and batch reprocessing do not create a decision boundary for human routing.

Question 35Plan and design AI solutions

A company wants an AI assistant to answer questions using data that must remain within its own subscription and must not be shared with the model provider for training. Which design consideration is most important?

  1. Enabling verbose logging of all prompts
  2. Choosing an offering with contractual data-use terms that exclude training on customer data Correct answer.
  3. Deploying the assistant in the most inexpensive region
  4. Selecting the model with the largest context window

Explanation

Data-handling commitments are established through the service's contractual terms and configuration, not by model size or region. Verbose prompt logging would increase exposure rather than protect it.

Question 36Plan and design AI solutions

A solution must support a conversational experience where the assistant remembers details from earlier in the same session. Which design element provides this capability?

  1. Increasing the maximum output token limit
  2. Disabling content safety checks for the session
  3. Maintaining a session-scoped conversation history included in each model request Correct answer.
  4. Storing all conversations permanently in the retrieval index

Explanation

Short-term memory is achieved by including prior turns of the current session in the request context. Permanent indexing, output limits, and disabling safety do not provide conversational continuity.

Question 37Plan and design AI solutions

A design specifies that the AI solution must degrade gracefully when the primary model endpoint is throttled. Which approach best satisfies this requirement?

  1. Cache only the system prompt locally
  2. Send requests to the endpoint more frequently to warm it up
  3. Implement retry with backoff and fall back to a secondary model deployment Correct answer.
  4. Remove all rate limiting from the client

Explanation

Retry with backoff handles transient throttling, and a secondary deployment provides continuity if the primary remains unavailable. Removing limits, increasing request rate, or caching only the prompt does not prevent failure under throttling.

Question 38Plan and design AI solutions

A team wants to evaluate whether a planned AI solution will meet latency targets before full build-out. Which approach is most appropriate?

  1. Estimate latency from the model's parameter count alone
  2. Build a prototype that measures end-to-end latency with representative inputs Correct answer.
  3. Defer latency testing until after production deployment
  4. Assume latency equals the sum of documented service limits

Explanation

End-to-end latency depends on retrieval, orchestration, and model response time, so a prototype with representative inputs gives reliable measurements. Parameter count, summed limits, and post-deployment testing do not validate the target beforehand.

Question 39Plan and design AI solutions

A solution must extract structured fields such as invoice number, date, and total from scanned invoices. Which capability should the design rely on?

  1. Text translation of the invoice into another language
  2. Document intelligence that returns key-value pairs from forms Correct answer.
  3. Speech-to-text transcription of the invoice
  4. Sentiment analysis on the invoice text

Explanation

Form-oriented document processing is designed to return structured fields from scanned documents. Sentiment, transcription, and translation address different tasks and do not extract invoice fields.

Question 40Plan and design AI solutions

A design must ensure that a retrieval index stays current as source documents are added, updated, and deleted. Which approach best addresses this?

  1. Manual reindexing requested by users when answers seem stale
  2. A full reindex performed once at initial deployment
  3. An incremental indexing pipeline triggered by document change events Correct answer.
  4. Caching retrieval results indefinitely to reduce load

Explanation

Event-driven incremental indexing keeps the index synchronized with source changes, including deletions. One-time reindexing, manual requests, and indefinite caching allow the index to drift from the source.

Question 41Build and configure AI agents and workflows

In a Microsoft Copilot Studio topic, which element determines the specific user phrases that trigger the topic?

  1. Question nodes
  2. Message nodes
  3. Condition branches
  4. Trigger phrases Correct answer.

Explanation

A topic is entered when the user's message matches one of its trigger phrases, which the author supplies as example utterances. Other nodes control conversation flow after the topic is entered, not entry itself.

Question 42Build and configure AI agents and workflows

You need a value captured in one topic to remain available later in the same conversation so another topic can use it. What should you do with the variable?

  1. Store it in a message node
  2. Reset it at the end of the topic
  3. Convert it to a topic-level variable
  4. Mark it as a global variable Correct answer.

Explanation

Global variables persist across topics for the duration of the conversation, so any later topic can read them. Topic-level variables are scoped to a single topic and are not reliable across topic boundaries.

Question 43Build and configure AI agents and workflows

What is the primary purpose of a knowledge source in an agent?

  1. To define the visual theme of the chat canvas
  2. To supply grounding content the agent can search when answering Correct answer.
  3. To authenticate users before the conversation starts
  4. To schedule when the agent is published

Explanation

Knowledge sources provide the content an agent retrieves and cites so answers are grounded in authoritative material. Presentation, publishing schedules, and authentication are handled by other configuration areas.

Question 44Build and configure AI agents and workflows

An agent should hand a conversation to a human agent when the user explicitly asks for a person. Which configuration supports this?

  1. A shorter conversation timeout value
  2. A higher creativity setting on the model
  3. An additional trigger phrase on the greeting topic
  4. A handoff or escalate action configured for the topic Correct answer.

Explanation

Handoff is implemented by an explicit escalation path, such as a topic with a handoff action that transfers the conversation to a live queue. Model creativity, triggers, and timeouts do not route work to people.

Question 45Build and configure AI agents and workflows

A workflow must run automatically whenever a new item is added to a SharePoint list. Which trigger type fits this requirement?

  1. An automated trigger tied to the list event Correct answer.
  2. A manual trigger started by the user
  3. A scheduled recurrence trigger
  4. A button trigger inside a chat client

Explanation

Automated triggers fire in response to a defined event such as item creation, which matches the requirement. Manual, scheduled, and button triggers require a person or a clock rather than the event itself.

Question 46Build and configure AI agents and workflows

Which action type in a cloud flow should you use to call an agent and use its response in later steps?

  1. A compose action that builds a string
  2. A terminate action that ends the run
  3. A delay action that pauses execution
  4. An agent action that returns output to the flow Correct answer.

Explanation

Agent actions invoke an agent and expose its response as dynamic content for subsequent steps. Compose, delay, and terminate actions do not call an agent.

Question 47Build and configure AI agents and workflows

What does an agent's system message primarily control?

  1. The retention period for conversation transcripts
  2. The agent's persona, tone, and behavioral boundaries Correct answer.
  3. The network region where the service runs
  4. The list of channels where the agent is published

Explanation

The system message sets instructions that shape how the agent behaves, including tone, scope, and constraints. Channels, retention, and hosting region are governed by separate settings.

Question 48Build and configure AI agents and workflows

You want an agent to answer only from approved internal documents and decline unrelated questions. Which setting most directly enforces this boundary?

  1. Increasing the number of trigger phrases on every topic
  2. Restricting the agent to its configured knowledge and instructing it to decline off-topic requests Correct answer.
  3. Adding more channels to the agent
  4. Enabling a longer session timeout

Explanation

Grounding to configured knowledge plus explicit instructions to decline out-of-scope requests keeps answers within approved material. Triggers, timeouts, and channels do not constrain the content of answers.

Question 49Build and configure AI agents and workflows

A topic collects an order number, then must branch to different messages depending on whether the number exists in a data source. Which combination achieves this?

  1. A question node storing the value, followed by a condition node that tests the lookup result Correct answer.
  2. A message node followed by a redirect to another topic
  3. Two trigger phrases on the same topic
  4. An end conversation node placed before the question

Explanation

The question node captures the value into a variable, and a condition node evaluates it or a lookup result to choose a branch. Messages, triggers, and early termination do not provide branching logic.

Question 50Build and configure AI agents and workflows

Users report the agent answers general questions well but never starts the topic that handles refunds. What should you check first?

  1. Whether the agent has a handoff action configured
  2. Whether the refund topic's trigger phrases match how users actually phrase requests Correct answer.
  3. Whether the environment has multiple channels enabled
  4. Whether the refund topic has too many condition nodes

Explanation

A topic that never starts usually has trigger phrases that do not match real user wording, so the utterance is routed elsewhere. Conditions only matter after the topic begins, and handoff or channels do not affect topic matching.