Free AB-620 Practice Test | 76 Real Exam-Style Questions 2026

Microsoft AB-620 Practice Test

An AB-620 practice test helps you check whether you can design, integrate, test, and manage enterprise AI agents in Microsoft Copilot Studio—not simply recognize feature names. You can Discover free certification practice tests to explore more exam preparation, then use this page to understand the current AB-620 objectives, practise realistic decisions, and create a focused study plan for the Microsoft Certified: AI Agent Builder Associate exam.

What is the Microsoft AB-620 exam?

AB-620 is the certification exam for Microsoft Certified: AI Agent Builder Associate. It measures whether professional developers and advanced builders can create scalable, integrated AI agent solutions with Microsoft Copilot Studio, Microsoft Power Platform, Azure, Microsoft 365 Copilot, Microsoft Foundry, and enterprise technologies.

The exam goes beyond building a simple question-and-answer agent. Candidates must plan secure agent architectures, connect business systems and knowledge sources, configure advanced topics and flows, add tools, create multi-agent solutions, test performance, monitor behavior, and move solutions between environments.

Microsoft classifies the certification as intermediate. The official AI Agent Builder Associate page recommends familiarity with Power Fx, Microsoft Dataverse, Power Platform environments, Microsoft 365 Copilot, Microsoft Foundry, and adaptive cards. Candidates should also understand generative AI, orchestration, retrieval-augmented generation, prompt engineering, REST APIs, Model Context Protocol, and Agent2Agent communication.

Who should take AB-620?

AB-620 is aimed at people who build enterprise-ready agents rather than users who only interact with Microsoft Copilot. It may be a suitable certification for:

• Professional developers extending Copilot Studio with APIs and enterprise systems
• Advanced low-code builders creating production agent solutions
• App makers who use Power Fx, Dataverse, connectors, flows, and solutions
• Consultants designing AI agents for customers or internal departments
• ISV partners integrating their services with the Microsoft agent ecosystem
• Power Platform developers moving from simple agents to advanced integrations
• AI solution builders working with RAG, MCP, A2A, Microsoft Foundry, or Fabric
• Developers responsible for agent testing, monitoring, deployment, and lifecycle management

This is not a basic Microsoft Copilot usage exam. Students should already know how to configure a Copilot Studio agent with instructions, topics, tools, and ordinary knowledge sources. If those foundations are new, build several small agents before beginning advanced AB-620 practice.

If you are comparing this credential with other Microsoft paths, Practice for your next Microsoft certification and select an exam that matches your current technical experience.

Recommended knowledge before studying AB-620

Microsoft does not list another certification as a formal prerequisite. However, the audience profile describes a broad practical background. Before attempting full mock tests, you should understand:

• Basic Copilot Studio agent creation and publishing
• Instructions, topics, trigger behavior, tools, and knowledge sources
• Microsoft Power Platform environments and solutions
• Dataverse concepts and connector-based integration
• Basic Power Fx expressions and variables
• Prompt engineering and responsible AI principles
• REST methods, requests, responses, authentication, and OpenAPI descriptions
• Generative AI models, context, orchestration, grounding, and RAG
• The purpose of MCP and A2A connections
• Application lifecycle management across development, test, and production environments

You do not need to be an expert in every Microsoft product. You do need enough hands-on experience to recognize how identity, data, permissions, orchestration, testing, and deployment fit together in a production agent solution.

What should an AB-620 practice test measure?

A useful AB-620 practice test should measure design and implementation judgment. It should ask you to choose an appropriate integration, authentication approach, workflow, tool, evaluation method, or deployment component for a stated business requirement.

Good questions should help you practise the ability to:

1. Translate a business process into an agent architecture.
2. Choose a suitable identity and permission strategy.
3. Decide when human approval is required.
4. Connect an agent to enterprise knowledge and services.
5. Compare connectors, REST APIs, MCP tools, and connected agents.
6. Configure topics, variables, prompts, cards, flows, and error handling.
7. Design agent-to-agent collaboration without unnecessary complexity.
8. Monitor and evaluate output quality, reliability, and performance.
9. Package and deploy an agent through managed environments.
10. Apply security, governance, and responsible AI controls throughout the lifecycle.

Memorizing the names of Microsoft products is not enough. The exam expects you to understand what each component does and why it is suitable for a particular enterprise scenario.

Current Microsoft AB-620 exam domains

The official AB-620 study guide defines three domains:

The integration-and-extension domain has the highest weighting. However, a realistic exam scenario may combine planning, integration, security, testing, and lifecycle management in one problem.

Domain 1: Plan and configure agent solutions — 30–35%

This domain covers solution planning, identity, channels, responsible AI, governance, agent flows, topics, response design, APIs, adaptive cards, and variables.

Plan an enterprise agent solution

Begin by identifying the user, business goal, systems involved, allowed actions, required data, and success criteria. An agent for employees may use organizational identity and internal data, while an external customer agent may require different authentication, data boundaries, channels, and safety controls.

An effective plan should address:

• Audience: Is the agent for employees, customers, partners, or a mixed group?
• Identity: Does an action run as the user, the agent author, an application identity, or another approved principal?
• Authorization: What data and actions may each user access?
• Channels: Will the agent appear in Microsoft Teams, Microsoft 365 Copilot, a website, or another supported channel?
• Enterprise integration: Which systems provide knowledge or perform actions?
• Governance: Which environment, data policy, ownership, review, and auditing rules apply?
• Responsible AI: What risks, limitations, disclosures, approvals, and fallback behavior are required?
• Reuse: Which topics, tools, flows, prompts, connectors, or child agents can become reusable components?

Do not select a technology before understanding the requirement. For example, a REST API may be appropriate for a direct system action, while A2A is more suitable when another agent has its own reasoning and domain workflow.

Identity, security, and governance

Identity planning is central to enterprise agents. A user-provided connection can preserve the user’s permissions when a tool accesses data. A maker-provided connection may centralize execution but can expose broader access if used carelessly. The safest choice follows least privilege and the organization’s identity architecture.

Security planning should cover data sensitivity, connector permissions, authentication, secret management, environment access, data loss prevention, and logging. Responsible AI planning should include human oversight for high-impact decisions, clear limitations, testing for harmful or inaccurate outputs, and a safe response when the agent cannot complete a request confidently.

Agent flows

Agent flows automate repeatable processes and integrate apps or services. They can be created in Copilot Studio and called by an agent as tools. A flow normally accepts inputs, performs one or more actions, and returns outputs.

For the exam, know how to:

• Create and trigger an agent flow
• Add input and output parameters
• Configure actions and connectors
• Add a flow to an agent or topic
• Monitor flow runs
• Handle failures and return useful error information
• Include human approval when a process should not be fully autonomous

A human-in-the-loop flow is appropriate when a decision has financial, legal, security, employment, or other significant consequences. Human review can also be useful when the agent’s confidence is low or a request falls outside normal limits.

Microsoft’s agent-flow training explains that flows provide consistent execution and end-to-end process visibility. For exam questions, pay attention to whether the task requires natural-language reasoning, deterministic automation, or both.

Topics, prompts, tools, and responses

A topic represents a conversational path or business capability. It can use variables, conditions, messages, tools, prompts, flows, and generative-answer nodes.

You should be able to recognize when to:

• Add an agent flow to a topic
• Call a REST API or send an HTTP request
• Add a tool for an action
• Use a custom prompt for advanced response generation
• Ground an answer with a custom knowledge source
• Configure a generative answers node
• Format a response for clarity
• Present an adaptive card
• Store and pass information with variables

Adaptive cards present structured information and interactive elements in supported channels. Variables store values during a conversation or workflow. Clear names, correct scope, and predictable input and output types make both easier to maintain.

Domain 2: Integrate and extend agents in Copilot Studio — 40–45%

This is the largest AB-620 domain. It covers enterprise knowledge, connectors, Azure AI Search, computer use, MCP, REST APIs, multi-agent collaboration, Foundry, Fabric, A2A, custom models, and Application Insights.

Connect enterprise knowledge sources

Knowledge helps an agent answer questions using organizational information. The correct source depends on where the information is stored, how current it must be, who may access it, and whether access must follow each user’s identity.

The current exam includes:

• Microsoft Copilot connectors
• Microsoft Power Platform connectors
• Azure AI Search
• Enterprise systems such as ServiceNow or SAP
• Microsoft Fabric data agents
• Custom knowledge sources

Connecting a source is only part of the work. Builders must consider permissions, indexing or retrieval behavior, freshness, geographic and compliance boundaries, and how the agent should respond when the source contains no reliable answer.

Retrieval-augmented generation, or RAG, retrieves relevant information and includes it as grounding context for a generative response. RAG can improve relevance, but it does not guarantee correctness. The quality of the data, retrieval method, instructions, access controls, and evaluation process still matter.

Power Platform connectors, custom connectors, and REST API tools

A prebuilt Power Platform connector provides a supported interface to a known service. A custom connector describes an API that does not have a suitable prebuilt connector. A REST API tool can expose selected endpoints directly to an agent using a supported API definition and authentication configuration.

Choose based on the integration requirement:

• Use a prebuilt connector when an appropriate supported connector already exists.
• Use a custom connector when an organization needs a reusable Power Platform interface for its own API or service.
• Use a REST API tool when the agent needs selected API operations and the required OpenAPI information is available.
• Use a Send HTTP request action inside a controlled topic when a direct request is appropriate for that topic’s flow.

Microsoft’s Copilot Studio tools documentation lists connectors, agent flows, prompts, REST APIs, MCP, and computer use as different extension mechanisms. Good exam answers use the simplest supported tool that meets the security and reuse requirements.

Model Context Protocol tools

MCP is a protocol that lets compatible agents connect to tools and resources exposed by an MCP server. In Copilot Studio, an existing MCP server can be added through the supported onboarding experience or, in relevant cases, through a custom connector.

Study MCP as an integration decision, not just an acronym. Check:

• Which tools and resources does the server expose
• How the connection authenticates
• Which users or agents may call it
• Whether the server is trusted and approved
• What data leaves the Microsoft environment
• How permissions and errors are handled
• Whether a connector or a simple REST tool would be more suitable

The official MCP connection guide explains the supported connection methods. Apply least privilege and avoid exposing unnecessary tools to the agent.

Computer use

Computer use allows an agent to interact with a graphical interface by selecting buttons, choosing menu items, and entering data. It can help when a legacy or third-party system lacks a practical API.

Computer use should not automatically be the first integration choice. APIs and connectors are often more reliable, structured, scalable, and easier to govern. When computer use is required, monitor it, restrict its environment, test interface changes, protect credentials, handle unexpected screens, and add approval for sensitive actions.

Multi-agent solutions

A multi-agent solution separates responsibilities among specialized agents. One agent may coordinate the user interaction while another handles HR knowledge, finance analysis, Fabric data, or a specific enterprise process.

The current outline includes integration with:

• Other Copilot Studio agents
• Microsoft Foundry agents
• Microsoft Fabric data agents
• Existing external agents
• Agents that support the Agent2Agent protocol

Use multi-agent design when specialization, ownership, reuse, security boundaries, or independent lifecycle management provide a real advantage. Do not split a simple task across several agents only because the feature exists. Extra agents add routing, latency, testing, permission, and troubleshooting work.

A2A compared with MCP and APIs

The Agent2Agent protocol supports delegation from one agent to another agent that has its own capabilities and reasoning. MCP connects an agent to tools and resources. A REST API provides defined service operations.

Microsoft’s A2A documentation recommends A2A when integrating an external agent that already implements the protocol and owns domain-specific reasoning. Use an API or connector for a standard service call, and use MCP when the integration is naturally exposed as MCP tools or resources.

Microsoft Foundry, Azure AI Search, and model selection

Microsoft Foundry can supply advanced agent and model capabilities. AB-620 candidates should understand how Copilot Studio can integrate Foundry agents, use Azure AI Search to ground generative answers, and configure custom prompts to use models from the Foundry model catalog.

Model selection should consider capability, quality, latency, cost, safety, availability, and organizational policy. A larger or more expensive model is not always necessary. Test with representative prompts and choose a model that meets the solution’s measurable requirements.

Microsoft Fabric data agents

A Fabric data agent can give a Copilot Studio solution controlled access to analytical data. The integration requires attention to tenant alignment, user or author authentication, workspace permissions, data-source permissions, publishing status, and supported channels.

Some Fabric and connected-agent features may be in preview. Microsoft notes that widely used preview features can appear in certification exams. Students should understand the documented purpose and limitations without assuming a preview feature is suitable for every production deployment.

Monitor agents with Application Insights

Application Insights helps teams observe agent activity and diagnose performance or reliability problems. Monitoring can support investigation of failures, latency, usage patterns, dependencies, and other telemetry made available by the configured solution.

Monitoring should answer practical questions: Is the agent responding? Which dependency failed? Is latency increasing? Which flow or API returns errors? Are users reaching a fallback path? Telemetry must also respect privacy and data-retention requirements.

Domain 3: Test and manage agents — 20–25%

This domain covers agent evaluation and application lifecycle management.

Create representative test sets

A test set should represent the questions, tasks, language, user groups, edge cases, and failure conditions the agent will face. Do not use only simple prompts that the agent already handles well.

Include examples such as:

• Normal user requests
• Ambiguous questions
• Requests with missing information
• Unauthorized data requests
• Prompt-injection attempts
• Conflicting instructions
• Tool or dependency failures
• High-impact actions that require approval
• Out-of-scope questions
• Expected fallback and escalation behavior

Keep expected results clear enough to evaluate. A good test may check response correctness, grounding, tool selection, task completion, safety, tone, latency, or another measurable requirement.

Choose an evaluation method

Different goals require different evaluation methods. Automated evaluation supports repeatable checks across a larger set. Human evaluation is valuable for nuance, business suitability, safety, and user experience. Production telemetry reveals real usage patterns but should not replace testing before deployment.

Review both successful and failed results. A high average score can hide a dangerous failure in a small but important category. Group results by scenario, audience, language, tool, and risk level when useful.

Application lifecycle management

Application lifecycle management, or ALM, moves a solution through development, testing, approval, and production in a controlled way.

For AB-620, study how to:

• Create a Power Platform solution
• Add an existing agent and related components to the solution
• Separate environment-specific configuration with environment variables
• Use connection references appropriately
• Deploy through Microsoft Power Platform Pipelines
• Extend a pipeline where required
• Test after deployment
• Maintain ownership and version control practices

A solution packages related components. Environment variables prevent builders from hard-coding values such as endpoint URLs or identifiers that differ between development, test, and production. Power Platform Pipelines automate and govern deployment between environments. The official pipeline overview describes pipelines as an approachable way to bring ALM automation and CI/CD capabilities into Power Platform.

High-value AB-620 comparisons to remember

How Our AB-620 Practice Path Builds Production-Ready Skills

AB-620 preparation should strengthen the same decisions you will make while building real enterprise agents. Our practice structure helps you connect architecture, integration, testing, security, and deployment instead of learning each Microsoft feature in isolation.

When you prepare with us, you receive:

• Current domain coverage: Questions follow the three published AB-620 domains and their weightings.
• Integration-focused scenarios: Practice gives extra attention to the 40–45% integration-and-extension domain.
• Clear answer explanations: Rationales show why one pattern fits the requirement better than another.
• Progress by topic: Results help identify whether planning, flows, topics, APIs, MCP, multi-agent design, testing, or ALM need review.
• Student-friendly definitions: New agentic AI concepts are explained without removing the terminology required for the exam.
• Progressive difficulty: Begin with feature purpose, then move to architecture and troubleshooting scenarios.
• Timed mock attempts: Later practice helps you manage the 120-minute exam period calmly.
• Readiness checks: Consistent results across all domains provide a more useful signal than a single high score.

Do not aim to memorize every screen. Learn the purpose, prerequisites, limitations, identity behavior, and lifecycle of each component. When you are ready to turn study notes into active practice, Explore Edurely and use each result to select your next hands-on exercise.

How to use an AB-620 practice test effectively

Start with a diagnostic set

Take a short mixed quiz before deep study. Record your result for planning and configuration, integration and extension, and testing and management. The goal is to locate knowledge gaps, not produce an impressive first score.

Study one architecture at a time

Choose a small business process and draw its users, identity, knowledge, tools, agents, approvals, channels, monitoring, and deployment path. This makes individual services easier to remember.

Reproduce the concept in Copilot Studio

After learning a feature, configure a safe example. Add a variable, call a test flow, create a card, connect a tool, or package an agent in a solution. Remove unused paid resources and never place sensitive production data in a study environment.

Review every uncertain response

For each error or guess, record the requirement, correct component, reason it fits, and reason the alternative fails. A correct guess still represents unfinished learning.

Use fresh scenarios after a delay

Repeating the same set immediately measures memory of wording. Study the concept, wait, and answer a differently written scenario.

Add timed practice near exam day

Use fresh mixed questions and the official 120-minute limit. Microsoft does not publish a fixed question count, so practise steady progress instead of assuming a particular number of minutes per question.

A four-week AB-620 study plan

Week 1: Solution planning, security, and agent configuration

Study audiences, identity, channels, responsible AI, governance, and reusable components. Build a small agent with instructions, variables, a topic, a custom prompt, a generative answer, and an adaptive card. Draw the identity and data flow.

Weekly goal: Explain how business requirements influence identity, channels, knowledge, tools, approvals, and governance.

Week 2: Flows, connectors, APIs, and MCP

Create an agent flow with inputs, outputs, monitoring, and error handling. Add a safe connector tool. Review custom connectors, OpenAPI-based REST tools, HTTP requests, MCP servers, authentication choices, and least privilege. Design one human approval step.

Weekly goal: Select the simplest secure integration for a service, tool, or workflow requirement.

Week 3: Enterprise knowledge and multi-agent design

Study Copilot connectors, Power Platform connectors, Azure AI Search, RAG, Foundry, model selection, Fabric data agents, computer use, connected agents, and A2A. Draw a multi-agent architecture and justify every agent boundary.

Weekly goal: Compare knowledge, tools, APIs, MCP, A2A, Foundry agents, and Fabric data agents without confusing their purposes.

Week 4: Testing, monitoring, ALM, and timed practice

Create a test set with normal, edge, unauthorized, and failure scenarios. Compare automated and human evaluation. Review Application Insights, solutions, environment variables, connection references, and Power Platform Pipelines. Take at least two fresh timed mock tests on different days.

Weekly goal: Produce consistent scores across all three domains and explain why each answer fits the stated enterprise requirement.

Hands-on AB-620 practice activities

Use a safe development environment with non-sensitive data. Complete as many of these tasks as your licenses and permissions allow:

1. Build a Copilot Studio agent with clear instructions and scope.
2. Create an internal-user and external-user architecture comparison.
3. Add a topic with variables and conditions.
4. Format a response using an adaptive card.
5. Create an agent flow with typed inputs and outputs.
6. Add error handling and a useful failure response to the flow.
7. Add a human approval before a sensitive action.
8. Connect an approved Power Platform connector as a tool.
9. Review an OpenAPI document and identify possible REST operations.
10. Compare user-provided and maker-provided authentication.
11. Add a test REST tool or custom connector in a sandbox environment.
12. Review the tool list exposed by a trusted MCP server.
13. Design a case where computer use is justified and document its risks.
14. Add or study an Azure AI Search grounding architecture.
15. Compare Foundry model options using measurable requirements.
16. Design a parent agent with one specialized connected agent.
17. Explain when the specialist should be called and what context it receives.
18. Create a test set with expected outputs and safety cases.
19. Review evaluation results and group failures by category.
20. Add an agent and related components to a Power Platform solution.
21. Replace a hard-coded endpoint with an environment variable.
22. Review a development-to-test-to-production pipeline design.
23. Identify telemetry needed to troubleshoot errors and latency.
24. Document data retention, permissions, and responsible AI controls.

Common AB-620 preparation mistakes

Treating AB-620 as a basic agent-building exam

The certification targets professional developers and advanced builders. Simple instructions and a public website knowledge source do not cover enterprise integrations, protocols, monitoring, testing, and ALM.

Studying features without identity and permissions

Every connector, tool, knowledge source, and connected agent has an access model. Ask whose identity is used and whether that identity has only the required permissions.

Confusing knowledge with actions

Knowledge grounds an answer. A tool performs an operation. Some integrations can provide both information and action, but the solution should still make the purpose and permissions clear.

Choosing computer use before an API

Graphical automation can be useful for legacy systems, but it may be more fragile than a supported connector or API. Choose it because the requirement justifies it, not because it appears advanced.

Adding unnecessary agents

A multi-agent solution is not automatically better. Use separate agents when specialization, ownership, security, reuse, or lifecycle boundaries provide a measurable benefit.

Ignoring error and fallback paths

APIs fail, users lack permission, data can be missing, and model output can be wrong. Practise designing retry, fallback, escalation, and human review behaviour.

Testing only successful prompts

A useful test set includes ambiguous, unauthorized, unsafe, out-of-scope, and dependency-failure scenarios.

Hard-coding environment values

Development and production usually use different endpoints, identifiers, and connections. Environment variables and connection references make deployments safer and more maintainable.

Using unauthorized exam dumps

Leaked or copied questions can be inaccurate, outdated, and inconsistent with Microsoft’s certification rules. Use official objectives, documentation, hands-on labs, and original practice questions with explanations.

AB-620 exam-day tips

• Confirm the appointment time, time zone, identification, and delivery method.
• Register with a personal Microsoft account when possible so your exam history is not dependent on a work or school account.
• Check Pearson VUE’s current system and room requirements if testing online.
• Use the official exam sandbox before the appointment.
• Read each scenario for audience, identity, data, action, channel, risk, and deployment clues.
• Prefer least-privilege and governed designs over broad access.
• Distinguish a knowledge question from an action or delegation requirement.
• Watch for human-approval requirements in high-impact scenarios.
• Do not assume that the newest or most complex feature is always the correct option.
• Manage the 120-minute testing period steadily.
• Microsoft currently allows eligible Learn content during associate and expert role-based exams, but the timer continues and access is restricted. Treat it as a targeted lookup tool, not a replacement for preparation.
• Check the current retake policy before scheduling another attempt. Microsoft permits a first retake after 24 hours and applies longer waiting rules to later attempts.

Microsoft AB-620 frequently asked questions

What certification does AB-620 lead to?

AB-620 is the exam for Microsoft Certified: AI Agent Builder Associate.

What is the full name of the AB-620 exam?

The official study guide calls it Designing and Building Integrated AI Agent Solutions in Copilot Studio. Microsoft training uses the closely related title Design and build integrated AI agent solutions in Copilot Studio.

Is AB-620 a new exam?

Yes. Microsoft introduced AB-620 in 2026 as part of its newer agentic AI credential portfolio. Because the product and exam are new, students should check the official pages frequently for objective, training, and practice-assessment updates.

Is AB-620 still in beta?

The current certification page provides normal scheduling, exam time, languages, and certification information without displaying a beta label. Microsoft also states that its Practice Assessment is not currently available and is usually released within eight weeks after an exam leaves beta. Check the live page when booking because status can change.

Is the official AB-620 Practice Assessment available?

Not at the time of this article’s update. Microsoft’s certification page explicitly says it is not currently available. The exam sandbox is available, but it demonstrates the interface rather than assessing all AB-620 knowledge.

Is AB-620 suitable for beginners?

No. Microsoft classifies it as intermediate and describes candidates as professional developers or advanced builders. Beginners should first learn Copilot Studio basics, Power Platform environments, connectors, Dataverse, Power Fx, and generative AI concepts.

Are there formal prerequisites?

Microsoft does not list another certification as a mandatory prerequisite. Practical knowledge across Copilot Studio, Power Platform, APIs, generative AI, and enterprise integration is strongly recommended.

Do I need coding experience for AB-620?

You should be comfortable with REST APIs, OpenAPI descriptions, integration patterns, variables, Power Fx, and technical troubleshooting. The exam combines low-code configuration with developer-oriented integration skills.

How long is the AB-620 exam?

The current certification page gives candidates 120 minutes to complete the assessment. Allow additional appointment time for check-in, instructions, agreements, and feedback.

What score is required to pass AB-620?

The official study guide states that a scaled score of 700 or higher is required. A scaled score should not be interpreted as a guarantee that exactly 70% of questions must be correct.

How many questions are on AB-620?

Microsoft does not publish a fixed AB-620 question count. Its general guidance says most certification exams typically contain 40–60 questions, but the number varies as exams and delivery components change.

What question types appear on AB-620?

Microsoft protects exam security and does not promise specific formats. The exam may include interactive components. Use the official sandbox to learn representative navigation and interaction styles.

Can I take AB-620 online?

The exam is proctored and scheduled through Pearson VUE. Available delivery choices and requirements depend on the options shown during official scheduling for your location.

How much does AB-620 cost?

The official page calculates the price based on the country or region where the exam is proctored. Select your location on Microsoft’s page for the current amount.

Which languages are available for AB-620?

The current page lists English, Arabic (Saudi Arabia), Chinese (Simplified), Chinese (Traditional), French, German, Indonesian (Indonesia), Italian, Japanese, Korean, Portuguese (Brazil), Russian, and Spanish.

Is AB-620 open book?

It is not a traditional open-book exam. Microsoft’s current policy permits access to eligible content in the Microsoft Learn domain during associate and expert role-based exams. The timer continues, some Learn areas are unavailable, and external websites and personal materials are not allowed.

Does AB-620 cover MCP?

Yes. The exam outline includes configuring MCP tools. Understand server trust, authentication, permissions, exposed tools, data flow, monitoring, and when MCP is more suitable than another integration.

Does AB-620 cover Agent2Agent protocol?

Yes. Candidates should understand how to create multi-agent solutions using A2A and when agent delegation is more appropriate than calling an API or MCP tool.

Are Microsoft Foundry and Fabric included?

Yes. The outline includes integrating Foundry agents, Fabric data agents, Azure AI Search with Foundry, the Foundry model catalog, and Application Insights monitoring.

Does AB-620 include computer use?

Yes. Candidates should understand how to configure and monitor computer use and when graphical-interface automation is appropriate compared with APIs or connectors.

Does AB-620 include Power Platform ALM?

Yes. You should know solutions, adding agents to solutions, environment variables, and Microsoft Power Platform Pipelines.

How long should I study for AB-620?

An experienced Copilot Studio developer may need three to five weeks of focused review. A builder with limited API, multi-agent, or ALM experience may need eight to twelve weeks. Use domain-level results and hands-on completion rather than copying another student’s schedule.

How many practice tests should I take?

Start with a diagnostic quiz, use topic tests during study, and complete at least two fresh timed mock tests near exam day. Reviewing explanations and building the related feature is more valuable than repeating the same set many times.

Is Microsoft’s AB-620 instructor-led course available?

The official AB-620T00-A course page currently states that the three-day course will be available on September 18, 2026. Microsoft also links to self-directed learning. Confirm the live course page because availability dates can change.

What happens if I fail AB-620?

Review your score report, study the lowest domain, and complete related hands-on work before retesting. Microsoft currently requires a 24-hour wait after the first failed attempt and 14 days between later attempts, up to its stated annual attempt limit.