Pass the Microsoft Certified: Dynamics 365 Sales AI Consultant Associate AB-210 Questions and answers with Dumpstech

For Dynamics 365 Sales predictive lead scoring, the model cannot be created unless there is enough historical lead outcome data in the selected training window. Microsoft’s predictive lead scoring configuration requirement states that the organization must have at least 40 qualified leads and 40 disqualified leads in the selected training period. The official guidance specifically explains that if the model is trained with leads from the past three months, the organization needs “at least 40 qualified and 40 disqualified leads” created and closed during that period.

In the sandbox, AdventureWorks has 30 qualified leads and 20 disqualified leads. However, 10 of the qualified leads are older than three months, and the business requirement says predictive scoring must be enabled for leads created within the last three months. Therefore, only 20 qualified leads are usable for this model. The sandbox currently has 20 usable qualified leads and 20 disqualified leads. To meet the required threshold of 40 each, the company needs 20 more qualified leads and 20 more disqualified leads . Simply creating 40 new leads is not enough because predictive scoring requires outcome-classified leads, not merely open or newly created records.

References/topics: Configure predictive lead scoring; lead scoring model training data requirements; AI-driven lead prioritization in Dynamics 365 Sales.

The required fix is about visibility and security , not agent operating mode. In the scenario, production has EnableRoleBasedSystemViews set to true, which restricts system views based on role configuration. Because the business requirement says all sellers should be able to access disqualified leads , the role-based system view setting must be updated so sellers can access the view that exposes leads disqualified by the Sales Qualification Agent.

The second required action is to change Lead table permissions. The customized Salesperson role currently grants sellers read access only to leads they own. That is too restrictive because leads disqualified by the Sales Qualification Agent may not be owned by each seller. To let all sellers view those records, sellers need organization-level Read permission on the Lead table. Option A is wrong because upgrading the agent to research and engage mode affects how the agent researches and interacts with leads; it does not solve seller access to disqualified records. Option C is also wrong because the look-back period controls which historical leads the agent evaluates, not who can view disqualified leads.

References/topics: Sales Qualification Agent; role-based system views; Dataverse security roles; Lead table read access; AI-driven lead qualification.

Requirement

Component

Mountaineer range

Product family

Athlete package

Product bundle

Metal range

Product property

The Mountaineer range should be configured as a Product family because it represents a product classification hierarchy. Dynamics 365 Sales uses product families to organize related products, child products, and bundles under a parent structure. Microsoft’s product catalog guidance states that product families can contain child product families, products, and bundles in a hierarchy, which fits the mountaineer cycle range with economy and premium fitting variations.

The Athlete package should be configured as a Product bundle because it combines multiple sellable items: a cycle, connected devices, and subscription-based analytics services. A bundle is used when multiple products are sold together as one commercial package. Dynamics 365 Sales allows products to be associated with a bundle, including quantities and required or optional components.

The Metal range should be configured as a Product property because sellers must choose a configurable attribute—chrome, aluminum, or titanium—when adding the mountaineer cycle to an opportunity. Product properties define product characteristics such as size, color, or component, and can be used at run time when adding products to opportunities, quotes, orders, or invoices.

References/topics: Product catalog setup; product families; product bundles; product properties; opportunity product configuration.

Requirement

Tool

Perform purchase required by CFO

Microsoft 365 admin center

Configure Sandbox billing

Power Platform admin center

Configure Production billing

Microsoft 365 admin center

Why: Production requires reliable AI capacity so sellers are not blocked when prepaid Copilot capacity is depleted. The correct production setup is pay-as-you-go / billing policy configuration through the Microsoft 365 admin center . Azure portal is not the best answer here because the scenario says no Azure subscriptions are available , and Microsoft 365 admin center can be used for the billing policy workflow. Microsoft Agent 365 is for agent management/governance, not billing configuration.

Requirement

Configuration

Blueprints

Name the blueprint workspace and pin the workspace.

Questions

Create a business function with seeded prompts.

For Blueprints, the correct configuration is to name the blueprint workspace and pin the workspace. The requirement is not asking to regenerate analysis; it asks for a reliable way to return to frequently used research output. In Sales Research Agent, a generated blueprint exists inside a workspace, and Microsoft states that the workspace displays the workspace name, can be renamed, and can be switched from the workspace menu. That makes naming and pinning the workspace the correct operational pattern for reusable research access.

For Questions, the correct configuration is to create a business function with seeded prompts. Sales Research Agent business functions are designed to tailor research to a specific use case, and administrators can add starter prompts. Microsoft explains that starter prompts appear on the Sales Research Agent home page for quick access and that the full prompt is sent to the agent when selected. This directly satisfies the requirement to retain a reusable library of approved questions.

Do not select regenerate the blueprint because regeneration refreshes or recreates analysis, but it does not create a persistent shortcut to frequently used research. Do not select custom table or manual prompt questions in Sales Copilot because the native Sales Research Agent feature already supports reusable business-function prompts.

References/topics: Sales Research Agent; research blueprints; workspace management; business functions; seeded/starter prompts; intelligent opportunity research.

Requirement

Configuration

Advance the lead to the Development stage

Set the decision maker field as required.

Ensure that the default process is applied

Authorize the process for field sellers.

The lead qualification process should be controlled through the Lead to Opportunity Business Process Flow, because the case study states that field sellers use this existing process to manage leads. To prevent a lead from advancing to the Development stage until a decision maker is confirmed, configure the Decision Maker step as required in the business process flow. Microsoft’s business process flow guidance states that each stage contains steps mapped to columns, and a step can be made required so users must enter data before moving to the next stage. This stage-gating behavior directly satisfies the requirement that leads cannot progress until the decision maker is confirmed.

To ensure the correct process is applied for field sellers, authorize the business process flow for the field seller security role. Microsoft explains that business process flows can be associated with security roles so only users with those roles can view or use them, and that the first active process available for a user’s security role is applied by default according to process order.

Do not choose Power Automate to advance the lead; the requirement is to block advancement until a required qualification criterion is completed, not to automate progression. “Switch to a different process” is user action, not a configuration standard.

References/topics: Business process flows; stage-gating; Lead to Opportunity Sales Process; security role authorization; seller workflow standardization.

Requirement

Configuration

Automatically prioritize leads based on conversion probability

Predictive lead scoring

Ensure the lead scoring improvement requirement is met

Automatically retrain model

The correct capability for automatically prioritizing leads based on conversion probability is Predictive lead scoring . Dynamics 365 Sales predictive lead scoring assigns scores to leads so sellers can prioritize the leads most likely to qualify or convert. Microsoft’s Sales documentation states that predictive lead scoring helps sales teams prioritize leads based on scores and improve lead qualification outcomes. This directly matches Contoso’s requirement to guide sellers toward high-potential leads and reduce inconsistent manual prioritization across regions.

To meet the requirement that lead scoring must continuously improve based on historical sales outcomes, configure the model to automatically retrain . Microsoft’s predictive lead scoring guidance explains that retraining uses the latest leads in the organization to improve model accuracy, and automatic retraining allows the application to retrain the model every 15 days. This is the correct option because Contoso wants the scoring model to improve continuously as more closed lead outcome data becomes available.

“Lead scoring model” is too generic; the AI capability required is specifically predictive lead scoring. “Relationship intelligence” supports relationship analytics and engagement insights, but it does not score leads by conversion probability. “Configure forecast” applies to pipeline forecasting, not lead scoring accuracy.

References/topics: Predictive lead scoring; lead prioritization; scoring model accuracy; automatic model retraining; AI-driven lead qualification.

The correct answer is C . To review the Sales Close Agent behavior for an opportunity, you open an opportunity researched by the agent and select See full research . Microsoft’s current Dynamics 365 Sales documentation describes this flow: sellers open the My top opportunities from AI agent view, open an opportunity, review the summary section, and then select See full research to open the Opportunity research page , which contains the complete research insights and recommendations.

This page is the right place to understand what the agent is surfacing and why it is helping progress deals. The Opportunity research page includes deal importance, deal risks and mitigations, deal overview, key signals, and other research-driven insights. Option A is incomplete and incorrectly starts from Forecast; the documented entry point is the Opportunities area and the AI-agent opportunity view. Option B is not the best answer because Sales Agent Runs is used for operational run records and permissions, not the seller-facing full research output. Option D is fabricated; there is no requirement to configure the opportunity pipeline view to force the full research page into every opportunity side panel.

References/topics: Sales Close Agent Research mode; Sales Opportunity Agent; Opportunity research page; See full research; AI-generated opportunity insights and recommendations.

The correct answer is Goal metric . In Dynamics 365 Sales, the goal metric defines how goal performance is calculated. Microsoft explains that each goal uses a goal metric to determine how the goal is tracked, and goal metrics can track actual, in-progress, and custom values through rollup fields. For won opportunity revenue, the metric can use the Opportunity table as the source and roll up the actual value for opportunities that are closed as won.

The quarterly requirement is handled by the goal’s time period. The goal metric specifies the calculation logic, including the source table, source attribute, date attribute, and source status such as Won. Microsoft’s goal metric documentation states that the date attribute is validated against the goal time period, so records participate in the rollup only when their date falls between the goal start and end dates. A rollup query is not the best answer because it only applies additional filtering criteria to an existing goal metric; it does not create the core calculation.

References/topics: Dynamics 365 Sales goals; goal metrics; rollup fields; won opportunity calculations; quarterly goal tracking.

The correct agent type is Sales Qualification Agent: Research and engage . The requirement is specifically about inbound lead processing: researching incoming leads, generating outreach, autonomously contacting leads, following up, and evaluating qualification during the engagement process. Microsoft defines Sales Qualification Agent as the AI agent used to automate lead qualification in Dynamics 365 Sales, especially for high-volume inbound leads from sources such as websites, events, and webinars. In Research and engage mode, the agent researches the lead, evaluates fit using target customer profile and BANT criteria, sends personalized outreach emails, engages based on responses, sends follow-up emails, detects positive intent, and then hands promising leads to sellers.

Research-only mode is not enough because it generates a draft outreach email for seller review but does not send outreach emails or detect positive intent from responses. Microsoft’s mode comparison explicitly shows that BANT checking, sending outreach, detecting positive intent, and follow-up emails are available in Research and engage mode, not Research-only mode. Sales Close Agent options are wrong because they apply to opportunity/deal execution, not initial lead qualification.

References/topics: Sales Qualification Agent; Research and engage mode; lead research; outreach automation; BANT qualification; AI-driven lead prioritization.