Microsoft • AB-410
Microsoft Certified: Intelligent Applications Builder Associate (AB-410) Practice Test
This certification validates your ability to design, build, and implement AI-powered solutions using Microsoft Power Platform, leveraging Copilot, natural language prompts, and low-code tools. It demonstrates expertise in creating apps, data models, and cloud flows that integrate agents, AI models, and Copilot features.
Exam Details
Questions
600
Duration
120 minutes
Passing Score
700/1000
Difficulty
AssociateLast Updated
May 2026
Topics Covered
Design Power Platform Solutions with AI-Enabled ToolsBuild Data Models in DataverseCreate Model-Driven AppsCreate Canvas AppsCreate Cloud FlowsCreate Prompts and Models in AI HubImplement Business and Process Logic
Exam Domain Breakdown
Create a Foundation for Intelligent Applications28%
Create Intelligent Applications28%
Build Business Application Logic and Automation43%
Exam Overview
Microsoft Certified: Intelligent Applications Builder Associate (AB-410) validates the ability of Power Platform professionals to design, build, and implement AI-powered business solutions using Microsoft Copilot, natural language prompts, and low-code tools. Certified professionals demonstrate competency across the full breadth of Power Platform development: creating Dataverse data models, building model-driven and canvas apps, integrating agents and Copilot features, authoring cloud flows, and crafting prompts and AI models through AI Hub. The exam, currently in beta as of April 2026, is organized into three functional domains spanning solution design, intelligent application creation, and business logic automation.
This certification represents Microsoft's repositioning of the Power Platform developer role in an AI-first era, replacing the PL-200 (Power Platform Functional Consultant Associate), which retires August 31, 2026. Holders demonstrate they can collaborate effectively with environment administrators, governance teams, agent developers, and solution architects to deliver end-to-end intelligent solutions that combine low-code development with generative AI capabilities, responsible AI principles, and application lifecycle management (ALM) practices.
Who Should Take This Exam
AB-410 is designed for Power Platform professionals who build AI-powered solutions in enterprise environments—roles such as App Makers, Business Application Developers, Functional Consultants, and Power Platform Solution Builders. Ideal candidates already have hands-on experience with Power Apps, Power Automate, Dataverse, and Power Pages, and are now expanding their skill set to incorporate AI, Copilot Studio agents, and generative AI features into their solutions.
The certification is also relevant for Business Analysts and Functional Consultants who gather requirements and translate business processes into Power Platform implementations. Candidates typically work alongside environment administrators, solution architects, and governance teams and are expected to apply ALM strategies and responsible AI principles in their day-to-day work.
Prerequisites
Microsoft does not enforce formal prerequisites for AB-410, but candidates are expected to bring meaningful hands-on experience across several areas. Specifically, familiarity with using Copilot in Power Apps, Power Automate, Power Pages, and Dataverse is required, along with awareness of creating agents in Microsoft Copilot Studio and foundational knowledge of AI models and prompts in AI Hub. Candidates should be comfortable working with Dataverse as a core data platform, mapping business processes to flows or app capabilities, and using low-code automation including Power Fx.
Beyond AI-specific skills, candidates should understand environment governance, roles, security, and solution lifecycle steps including ALM pipelines. Prior real-world experience with canvas apps, model-driven apps, cloud flows, and Power Pages sites will be essential, as the exam tests applied skills rather than theoretical knowledge.
Exam Format
Exam AB-410 is a proctored assessment administered through Pearson VUE, available online or at a testing center. Candidates are given 120 minutes to complete the exam. The passing score is 700 on a scale of 1000. The exam is currently in beta, which means scoring is not immediate—Microsoft collects response data during the beta period before releasing scored results to candidates. The exam is available in English.
The assessment includes a mix of question types, which may include multiple choice, drag-and-drop, case studies, and interactive lab-based components. Microsoft does not publish an exact question count; the number of scored questions varies. Candidates who need additional time due to language differences (if the exam is not available in their preferred language) may request an extra 30 minutes. Retakes are permitted 24 hours after a first failed attempt.
Skills Measured
- 1.Create a Foundation for Intelligent Applications (25–30%): Covers designing Power Platform solutions using AI-enabled tools—including analyzing requirements, evaluating built-in agents, recommending extensibility and environment types, and applying ALM strategies. Also includes building data models in Dataverse: creating and configuring tables, columns, relationships, prompt columns, row summaries, views, forms, and security settings.
- 2.Create Intelligent Applications (25–30%): Covers creating model-driven apps (forms, views, generative pages using natural language, charts, dashboards, and access configuration) and creating canvas apps (building from data, designing for accessibility and responsiveness, reusable components, named formulas, user-defined functions, component libraries, variables, collections, error handling, testing with Monitor, and creating Copilot Studio agents from canvas apps).
- 3.Build Business Application Logic and Automation (40–45%): Covers creating cloud flows (triggers, connectors, approvals, flow control with conditions and loops, testing and troubleshooting), creating prompts and AI models in AI Hub (building prompts from templates, adding knowledge and inputs, customizing model settings, consuming prompts and AI models in apps and flows), and implementing business and process logic (business rules, business process flows, calculated/rollup/formula columns, and evaluating logic use cases).
Study Tips
- Use the official AB-410 Study Guide on Microsoft Learn (learn.microsoft.com/credentials/certifications/resources/study-guides/ab-410) as your primary roadmap—each domain's sub-objectives directly map to exam questions, so work through each bullet systematically.
- Prioritize the 'Build Business Application Logic and Automation' domain (40–45% of the exam): spend dedicated time creating cloud flows with real connectors, building prompts in AI Hub from blank and from templates, and configuring business rules and process flows in Dataverse.
- Complete hands-on labs in a free Power Platform developer environment—create Dataverse tables with prompt columns and row summaries, build a model-driven app with generative pages using natural language, and integrate a Copilot Studio agent into a canvas app to reinforce the AI-integration objectives.
- Study the official Microsoft Power Platform documentation and Microsoft Copilot Studio documentation referenced in the study guide, paying special attention to AI Hub capabilities, prompt engineering, and consuming AI models in both apps and cloud flows.
- Use the Microsoft Exam Sandbox (aka.ms/examdemo) before your exam date to familiarize yourself with the user interface and interactive question types—AB-410 may include lab components that require live configuration in a simulated Power Platform environment.
- Review ALM concepts including solutions, pipelines, environment strategy, and responsible AI governance principles, as these cross-cutting topics appear within the foundation domain and are tested in the context of real deployment decisions.
- Join the Power Platform Community (community.powerplatform.com) and Microsoft 365 Copilot Community Hub on Tech Community to access peer discussions, scenario walkthroughs, and shared exam preparation resources relevant to the latest AI-enabled Power Platform features.
Career Benefits
AB-410 positions professionals at the intersection of low-code development and enterprise AI adoption—one of the highest-demand skill sets in the Microsoft ecosystem as organizations accelerate Power Platform deployments integrated with Copilot and generative AI. The certification directly replaces PL-200 (retiring August 2026), signaling that Microsoft considers AI-first app building the new baseline for Power Platform practitioners. Job roles that benefit include Power Platform Developer, Business Application Consultant, AI Solutions Builder, and Citizen Developer Lead.
As part of Microsoft's new AB-series certification path, AB-410 serves as the Associate-level entry point into a structured track: candidates can progress to AB-620 (Agentic AI Business Solutions Engineer) for deeper agent specialization or AB-100 (Agentic AI Business Solutions Architect) for expert-level solution architecture. This progression path reflects enterprise demand for professionals who can deliver end-to-end intelligent automation, making AB-410 holders well-positioned for roles in digital transformation, enterprise AI enablement, and Power Platform governance.
Sample Questions
Preview — answers shown5 sample questions with correct answers and explanations. Start a practice session to test yourself across all 600 questions.
1. Fabrikam's customer experience team is building a Power Pages website with an embedded Copilot Studio agent to handle product inquiries and order status lookups. The agent must retrieve customer order records stored in Dataverse. A Power Platform architect is advising the team on what must be addressed before the deployment is complete. Which two statements accurately describe how Copilot Studio agents behave when published to Power Pages? (Select two!)
Multiple correct answersAPower Pages is a supported publishing channel for Copilot Studio agents, enabling organizations to embed conversational experiences on external-facing websites that serve both anonymous and authenticated visitors
BPublishing a Copilot Studio agent to Power Pages automatically provisions the agent with organization-level Dataverse access, removing the need to configure security roles for data retrieval
CFor a Copilot Studio agent to retrieve Dataverse records on behalf of website visitors, data access permissions must be explicitly configured through Dataverse security roles and are not automatically granted by the embedding process
DCopilot Studio agents embedded in Power Pages are restricted to SharePoint document libraries as their sole knowledge source and cannot query Dataverse tables or index public website content
ECopilot Studio agents deployed to Power Pages can only serve authenticated users; the channel does not support anonymous visitor interactions regardless of the Power Pages site authentication settings
Explanation
Power Pages is a fully supported publishing channel for Copilot Studio agents. Organizations can embed a conversational agent directly into an external-facing Power Pages website to serve customers and other external parties. Power Pages supports a broad range of visitor identity scenarios, including anonymous browsing and authenticated sessions using various identity providers. A critical architectural requirement is that publishing an agent to Power Pages does not automatically provision Dataverse data access. When the agent needs to retrieve records — such as customer orders — the underlying data permissions must be explicitly designed and configured through the Dataverse security model. The embedding process itself is separate from access governance. Copilot Studio supports multiple knowledge source types beyond SharePoint, including public website URLs, uploaded documents, FAQ content, and Dataverse tables. The anonymous visitor restriction described is also incorrect — Power Pages explicitly supports anonymous browsing, and agents can be configured to respond to unauthenticated visitors depending on the site's authentication settings.
2. Southridge Video's Power Platform administrator is configuring Power Platform Pipelines to manage deployments across a three-stage chain: Development, QA, and Production. Before creating the pipeline, the administrator needs to confirm the Managed Environment requirements for each participating environment. Which two statements accurately describe the infrastructure requirements for Power Platform Pipelines? (Select two!)
Multiple correct answersAThe pipeline host environment must be designated as a Managed Environment before any pipelines can be created within it
BAll target environments configured within the pipeline, including QA and Production target environments, must be Managed Environments
CThe host environment can be a standard Production environment and does not require Managed Environment designation
DPipeline deployment stages can be executed out of order, allowing the Production stage to skip ahead of QA if an emergency approval is granted
EDeveloper environments used as the pipeline deployment source must be converted to Managed Environments before deployments can be initiated
Explanation
Power Platform Pipelines have distinct Managed Environment requirements depending on the role each environment plays. The host environment, which manages and orchestrates all pipeline activity, can be a standard Production environment and does not require Managed Environment designation. All target environments participating in the pipeline, including QA, staging, and production destination environments where solutions are deployed, must be Managed Environments. Starting February 2026, Microsoft automatically enforces Managed Environment status on pipeline target environments. Deployment stages within a pipeline must execute sequentially in the defined order and cannot be reordered or skipped; every stage must complete before proceeding to the next. Developer environments used as the deployment source do not require Managed Environment designation and can operate under Developer Plan licenses.
3. Litware Consumer Goods has a canvas app connected to a Dataverse table containing 600,000 product records. A maker writes a formula using the Search() function with Contains to find products whose description includes a specific keyword. During testing, only a small fraction of matching records are returned even when many qualifying records exist. What is the root cause of this behavior? (Select one!)
AThe Dataverse table requires column-level security to be disabled before full-text search is permitted across all rows
BThe canvas app has reached its maximum concurrent Dataverse connection limit, truncating the result set
CThe Search() function requires an explicit Sort() call before Contains evaluation can execute against the full dataset
DThe Contains function is not delegable in Dataverse, so the canvas app retrieves only the first 500 rows and filters them locally
Explanation
Delegation pushes data filtering to the Dataverse server so that only matching rows are transferred over the network. The Contains function is not delegable against Dataverse because it requires a full-table scan equivalent to SQL LIKE '%term%', which cannot be executed server-side. Canvas Apps therefore retrieve only the first 500 rows by default (configurable up to a maximum of 2,000) and apply the Contains filter client-side, producing an incomplete result set. The correct remediation is to replace Contains with StartsWith, which IS delegable against Dataverse because it maps to a SQL LIKE 'term%' index seek and is processed entirely on the server. Column-level security controls field visibility and has no bearing on delegation behavior. Adding a Sort() call does not affect whether a filter function is delegable. Concurrent connection limits are unrelated to the row-count truncation caused by non-delegable functions.
4. City Power & Light is deploying a canvas app solution from its Development environment to Production using Power Platform Pipelines. The solution contains an environment variable of type Text that stores the REST API endpoint URL for an external billing system. The endpoint URL differs between Development and Production. How should the team manage the environment variable value across environments to follow Power Platform ALM best practices? (Select one!)
AThe environment variable Definition travels with the solution during deployment; the Current Value must be set separately in each target environment
BThe environment variable data type can be changed from Text to Secret after the solution is deployed to Production in order to protect the billing endpoint URL
CEnvironment variable current values are automatically synchronized to all target environments during a Power Platform Pipelines deployment run and do not require manual configuration
DText-type environment variables do not support different values across environments and a separate environment variable must be created for each deployment target
Explanation
Environment variables consist of two distinct components: the Definition, which includes the schema, data type, display name, and optional default value, and the Current Value, which holds the environment-specific setting. During solution deployment through Power Platform Pipelines, only the Definition travels with the solution. The Current Value is intentionally excluded from the solution package and must be configured separately in each target environment. Power Platform Pipelines prompt administrators to provide or confirm environment variable values for the target environment at deployment time, enabling different endpoint URLs per environment without modifying any solution component. Current values are not automatically synchronized across environments; this separation is by design to support environment-specific configuration as a core ALM principle. Environment variable data types are immutable after creation. A Text-type variable cannot be changed to Secret or any other type after the variable is created, regardless of which environment it is deployed to. Environment variables are purpose-built to hold different values per environment, which is their primary ALM value, eliminating any need to create separate variables per deployment target.
5. Contoso Financial is deploying a model-driven app for loan officers to manage customer applications. The business requirement is for loan officers to use natural language to summarize loan records and draft follow-up emails directly within the app interface. An IT administrator needs to enable this capability. Which two conditions must be satisfied for the Copilot sidecar to function correctly in this model-driven app? (Select two!)
Multiple correct answersAThe Power Platform environment must not be hosted in a GCC, GCC High, or DoD sovereign cloud
BThe Copilot sidecar feature must be enabled in Power Platform admin center under Environments, Settings, and Features
CA custom Dataverse plug-in must be developed to expose record summarization through the Dataverse API
DLoan officers must be assigned the System Administrator security role to access Copilot sidecar functionality
EThe model-driven app must first be exported and reimported as a canvas app before Copilot features become available
Explanation
The Copilot sidecar in model-driven apps has two mandatory prerequisites: the environment must not be a sovereign government cloud, since Copilot sidecar is explicitly unavailable in GCC, GCC High, and DoD environments, and the feature must be explicitly enabled through the Power Platform admin center under Environments, Settings, and then Features. No custom plug-in development is required since the sidecar uses built-in AI Builder-powered capabilities for record summarization, email drafting, and natural language queries. Standard user security roles are sufficient to access the sidecar — System Administrator is not required and would represent an over-permissioned approach that violates least-privilege principles. Model-driven apps support the Copilot sidecar natively and do not require conversion to canvas apps; in fact, canvas and model-driven apps have separate and distinct AI integration patterns.
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