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| Section | Weight | Objectives |
|---|---|---|
| Identify benefits, capabilities, and opportunities for Microsoft's AI apps and services | 35–40% | - Aligning Microsoft AI tools to business requirements - Microsoft Copilot Studio capabilities - Microsoft 365 Copilot features and use cases - Azure AI services and Azure AI Foundry tools |
| Identify the business value of generative AI solutions | 35–40% | - Business benefits, ROI, and efficiency gains - Selecting generative AI solutions for business needs - Foundational concepts of generative AI - Differences between generative AI and other AI types |
| Identify an implementation and adoption strategy for Microsoft's AI apps and services | 20–25% | - Organizational readiness and change management - Adoption planning and scaling AI solutions - Measuring success and continuous improvement - Responsible AI principles and governance |
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NEW QUESTION # 67
Hotspot Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: No
A text-to-image generator (like DALL-E or Midjourney) takes textual descriptions and synthesizes them into visual imagery. It does not perform language translation workflows; that task requires natural language processing (NLP) or large language models (LLMs).
Box 2: No
Predictive analytics models rely on historical data and machine learning algorithms to forecast future trends, behaviors, or numerical outcomes (such as click-through rates or future sales).
They do not create or synthesize brand-new creative artifacts like marketing text or ad copies; that is the role of Generative AI.
Box 3: Yes
Generative AI chatbots (like those built using custom LLMs or Copilot Studio) excel at maintaining dynamic, human-like context. They can handle highly personalized conversations based on user profile inputs and dynamically synthesize relevant product recommendations.
NEW QUESTION # 68
Select the answer that correctly completes the sentence.
Prompt engineering is the process of __________.
Answer:
Explanation:
Explanation:
crafting clear instructions to guide generative AI solutions in generating context-appropriate content.
Prompt engineering is fundamentally about how you communicate intent to a generative AI model so it produces outputs that meet business expectations. The best completion is "crafting clear instructions to guide generative AI solutions in generating context-appropriate content" because it captures the practical, day-to- day discipline: shaping the input (prompt) with the right task framing, constraints, context, and output format.
In real deployments, prompt engineering includes specifying the role and objective (for example, "act as a customer support agent"), providing the necessary context (product details, policy excerpts, audience), adding explicit requirements (tone, length, must/must-not statements), and defining structured output (JSON fields, bullet sections, headings). It can also include adding examples (few-shot prompting), clarifying what to do when information is missing, and instructing the model to cite only provided sources or to ask follow-up questions. These techniques reduce ambiguity, improve consistency, and lower the risk of hallucinations or off-brand responses.
The other options are not accurate definitions. "Integrating AI-powered tools into business workflows" describes solution adoption/integration, not prompt engineering. "Identifying and fixing errors in AI- generated content" is review/editing or quality assurance. "Designing, developing, and training generative AI models" is model development/ML engineering. Prompt engineering operates without changing model weights ; it's about steering model behavior through well-constructed instructions and context.
NEW QUESTION # 69
Your company sells hiking and camping gear online.
You need a generative AI solution that can interact with customers, ask questions about their needs, and escalate to a human agent if necessary.
What solution should you use?
Answer: B
Explanation:
Generative AI chatbots function as a primary point of contact in modern customer service, using natural language processing (NLP) and large language models (LLMs) to engage in human-like dialogue rather than following rigid, pre-programmed scripts.
Reference:
https://cobbai.com/blog/ai-chatbot-for-customer-service
NEW QUESTION # 70
Your company manages a website that publishes daily news articles.
You need to recommend an AI solution that can analyze text and identify the main people, locations, and companies mentioned in the articles.
What should you include in the recommendation?
Answer: D
Explanation:
Azure Language in Foundry Tools can analyze text and identify main entities, including people, locations, and companies. This capability is officially known as Named Entity Recognition (NER).
Reference:
https://azure.microsoft.com/en-us/products/ai-foundry/tools/language
NEW QUESTION # 71
Your company manages an online catalog of office supplies.
You plan to use a generative AI solution to create product descriptions for your company's website. The solution must meet the following requirements:
- Ensure that the descriptions can be posted immediately after they are created.
- Enable the selection and inclusion of product details in each
description.
- Be fast and simple for non-technical staff to use.
What is the best type of solution to use? More than one answer choice may achieve the goal.
Select the BEST answer.
Answer: A
Explanation:
Using the Researcher agent within Microsoft 365 Copilot provides a highly effective solution for creating and immediately posting product descriptions. It allows non-technical staff to generate tailored, brand-aligned content by leveraging both internal product data and web research, allowing for immediate publication.
Reference:
https://learn.microsoft.com/en-us/dynamics365/business-central/ai-overview
NEW QUESTION # 72
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