AB-210 Accelerating Sales Pipelines with AI in Dynamics 365 Questions and Answers

The correct configuration is to set related record creation to Seller. The case study states that sales leadership requires flexibility in how leads are converted: inside sales need automatic opportunity creation, but field sellers need the option to manually decide whether an opportunity should be created when a lead is qualified. In the new lead qualification experience, Dynamics 365 Sales lets administrators control whether account, contact, and opportunity records are created automatically during lead qualification or whether sellers are prompted to choose which related records to create. Microsoft’s lead qualification guidance confirms that when automatic creation is not enabled, sellers are prompted to select which records should be created during qualification.

Option B and option E are wrong for field sellers because automatic creation would remove the manual decision point required by the case study. Option C is relevant to guiding sellers through sales stages, but the existing Lead to Opportunity Business Process Flow does not control whether related records are automatically created when a lead is qualified. Option D is unrelated because Copilot summaries help sellers review record information; they do not configure lead conversion behavior. Therefore, the required configuration for field sellers is Seller-controlled related record creation.

References/topics: Lead qualification experience; lead-to-opportunity conversion; related account, contact, and opportunity creation; Dynamics 365 Sales lead management.

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.

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.

Create a Power Automate cloud flow.

Add a Dataverse trigger.

Define an approval step.

Test and activate the flow.

The correct automation pattern is an automated Power Automate cloud flow triggered by a Dataverse event. The case study states that the process must notify the seller’s manager when a draft quote is created and requires approval, and that approvals must use the Power Automate Approvals connector. Therefore, the flow should first be created as a cloud flow, then started by a Dataverse trigger such as when a row is added, modified, or deleted on the Quote table, filtered for the draft quote condition. Microsoft’s Dataverse trigger guidance confirms that this trigger runs when a selected Dataverse table row is created, modified, or deleted.

After the trigger is defined, the flow must include an approval step using Power Automate approvals. Microsoft’s approval workflow guidance states that Power Automate can manage approvals across services including Dynamics 365 and Dataverse-based processes. The final action is to test and activate the flow so the quote approval automation is available to users. Do not use a scheduled trigger because the requirement is event-driven, not time-based. Do not connect to the existing desktop flow because that desktop flow processes partner orders for fulfillment, not draft quote approvals. A Teams step is optional collaboration, not the required approval mechanism.

References/topics: Power Automate cloud flows; Dataverse triggers; Approvals connector; Dynamics 365 Sales quote approval automation; sales platform extension.

The correct action is to select a valid price list on the opportunity and verify that the product has a matching price list item for the selected unit. Dynamics 365 Sales calculates Price Per Unit from the price list item when an existing catalog product is added to an opportunity, quote, order, or invoice. Microsoft states that if an existing product is associated with a price list, the price per unit is calculated from the related price list item; otherwise, it is set to 0 .

The failure pattern described in the question is classic missing or mismatched price-list setup. Price calculation will not occur when no price list is selected, when the selected price list does not contain the product, or when the required price list item is missing. Microsoft also notes that price lists tie the product, unit, and pricing details together. Option A is incomplete because matching currency alone does not create the product/unit price list item. Option B is wrong because User Provided revenue bypasses system calculation. Option D handles discounts only; it does not fix a zero base unit price.

References/topics: Opportunity products; price lists; price list items; Price Per Unit calculation; system-calculated opportunity revenue.

Requirement

Configuration

Open the Pipeline view by default in Opportunities

Configure Opportunity main form

Open a specific form for the opportunity side panel

Set the default Opportunity form

Ability to expand or collapse the grid by sections

Enable aggregation on view controls

Display the average value at the bottom of the grid

Enable aggregation on view controls

To open the Pipeline view by default, configure the Opportunity main form by adding the Pipeline view control for Opportunities. Microsoft states that the read-only grid is the default view for opportunities, but administrators can set the Opportunities pipeline view as the default by customizing the Opportunity table form and adding the Pipeline view component. The configuration includes selecting the Opportunities table, choosing the opportunity view, and enabling grouping and aggregation.

To open a specific form in the opportunity side panel, use Set the default Opportunity form . Microsoft’s configuration guidance states that when sellers open an opportunity from the pipeline view, the side panel displays opportunity details, and administrators can change the default side-panel form to the main opportunity form or a custom form.

For expanding/collapsing by sections such as Owner or Account and displaying average values at the bottom of the grid, enable aggregation/grouping behavior on the Pipeline view control. Microsoft states that Enable grouping and Enable aggregation allow sellers to group and aggregate opportunities in the pipeline view. This supports sectioned grid behavior and aggregate values such as average, sum, or count. The quick create form is irrelevant because it controls record creation, not pipeline display behavior.

References/topics: Opportunity pipeline view; Opportunity main form; side panel default form; grouping and aggregation; pipeline grid configuration.

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.

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

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.

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.