Generate Complaint Responses by Running an AI Hub Prompt
Short answer
B Run a prompt defined in AI Hub with the email content as dynamic inputs to generate the customer complaint response in Fabrikam's applications.
Question
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Background
Fabrikam Inc. is an energy provider that operates wind and solar farms across multiple countries and regions. The company uses Microsoft Power Platform to manage asset maintenance, technician workflows, and predictive analytics.
Field technicians use canvas apps on mobile devices to capture inspection and repair data. Operations managers use model-driven apps to monitor asset performance and maintenance history.
The company plans to enhance its platform by introducing AI-driven insights, improving reuse across applications, and establishing a formal application lifecycle management (ALM) strategy.
Current environment
Applications
• Field technicians use an outdated mobile app to log maintenance activities and capture asset readings in SharePoint Online.
• Operations managers use a model-driven app to review maintenance records and asset performance trends.
Development practices
• Developers build and modify applications directly in the production environment.
• There is NO structured ALM process.
• Solutions are NOT consistently used to package or deploy application components.
• Reusable components are inconsistently implemented across apps, leading to duplication.
AI integration
• Fabrikam Inc. plans to actively explore generative AI usage as part of the next phase of work.
Business requirement
Application development
• The outdated mobile app must be replaced with a new app that supports responsive design principles, provides full control over the UI, and allows technicians to take and upload photos directly from their mobile devices.
• The new app for the field technicians requires the name of the technician to be persisted on the home screen only. In addition, work orders must be displayed within a gallery.
• All new apps must connect to a scalable, cloud-based relational data store.
• Apps must support efficient data entry for technicians in the field.
• Reusable UI elements must be implemented to reduce duplication.
AI capabilities
• The company requires a generative AI solution to manage customer complaint responses and create custom inspection reports that align to an existing template.
• Customer complaint responses must be generated in applications and based on emails being sent to a mailbox.
• Custom AI development must be minimized.
Generative AI reusability
• Generative AI solutions must accept dynamic inputs to adapt to different scenarios.
• Generative AI solutions must be reusable across different Power Platform services.
Extensibility
• Custom UI form components must be reusable across applications.
• Use of server-side custom code must be minimized where possible.
Technical requirements
Application lifecycle management (ALM)
• Separate environments must be used for development, testing, and production.
• Solutions must be used to package application components, segmented based on functional areas.
• Managed solutions must be deployed to the production environment.
• Validation must occur before deployment to production.
Data processing
• Aggregated values across related rows must be displayed for reporting.
• Calculations must update automatically as new data is entered. Calculation data must be limited to a maximum length of 10.
Issues
• Duplicate logic exists across multiple canvas apps.
• Developers frequently overwrite changes in production.
• Generative AI solutions produce inconsistent outputs due to missing or inconsistent inputs.
• Maintenance metrics are not consistently calculated across related rows.
You need to generate the customer complaint response based on Fabrikam Inc.’s requirements.
Which action should you use?
Key Takeaways
The question tests choosing the generative text action that accepts dynamic inputs and runs across Power Platform services, not extraction or template-merge actions.
Fabrikam must generate customer complaint replies from incoming email using reusable generative AI with dynamic inputs; the correct action is to run an AI Hub prompt (option B).
Common mistake: Option A, Populate a Microsoft Word template, is tempting because the case mentions an existing template, but it only merges fixed data into a .docx and cannot compose a response from an email.
Expert Analysis
What the requirement is really asking
Fabrikam needs a customer complaint response that is generated from the body of an incoming email, delivered inside its applications, and driven by generative AI with as little custom development as possible. That is the textbook use of a prompt created in AI Hub (formerly AI Builder prompt library / Prompt builder), invoked through the Run a prompt action. So option B is the correct choice.
Why Run a prompt fits
A prompt defines its behaviour in natural language and exposes typed dynamic inputs — here the email subject, body, complaint category — plus outputs such as the drafted response. Because a prompt is a standalone, reusable AI asset, the same prompt can be executed from a Power Automate cloud flow triggered by "When a new email arrives", from a canvas app component, or from Copilot Studio. That satisfies the two stated generative AI requirements: dynamic inputs and reusability across Power Platform services, while minimizing custom AI development. It also addresses the reported issue of inconsistent AI outputs: named, validated inputs force every run to receive the same context.
Why the adjacent options are for different jobs
Option A, Populate a Microsoft Word template, merges known data into an existing.docx — it does not compose text. That is the answer for the other requirement in this case: creating the custom inspection report that must align to an existing template. Choosing A for complaint replies would produce merged fields, not a generated narrative.
Option C, Process documents, is AI Builder document processing, which extracts structured values from forms and documents — the wrong direction of data flow for text generation. Option D, Generate key phrases, only extracts salient terms from supplied text; it summarizes rather than drafts a reply.
What changes the answer
If the scenario asked to populate the fixed inspection report template with asset readings and technician name, the correct action would be A. If it asked to classify or extract data from uploaded inspection photos, C would apply. Read the verb — generate a response from email vs. fill a template vs. extract from documents.
Operational consequence of getting it wrong
Selecting A, C or D means no free-form customer reply is ever produced, forcing developers to hand-build server-side text generation code — violating the minimize-server-code and minimize-custom-AI requirements and reintroducing the inconsistent outputs the company is trying to eliminate.
Exam Strategy
Read the verb and the data direction first: generate/draft from text means a prompt action, extract/identify from documents means Process documents, and fill an existing file means Populate a Word template. Then check the reuse clause — wording such as 'dynamic inputs' and 'reusable across services' points to an AI Hub prompt asset rather than a connector-specific action.
Frequently Asked Questions
Why can't Populate a Microsoft Word template generate the complaint response?
How does running a prompt fix Fabrikam's inconsistent AI outputs?
Where can an AI Hub prompt be reused besides cloud flows?
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Discussion 1 contributions
Compiled from public community threads and reader submissions, lightly edited for clarity. Handles and vote tallies are shown as recorded, and comments reflect the views of individual contributors.
From public community threads 1
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ah2006 👍 1 Answered BDynamic text gegeneration => Run a prompt
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