Salesforce Salesforce-AI-Associate Lab Questions & Salesforce-AI-Associate Real Brain Dumps

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic	Details
Topic 1	AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.
Topic 2	AI Fundamentals: This topic discusses the major principles and applications of AI within Salesforce. It also focuses on different types of AI and their capabilities.
Topic 3	Ethical Considerations of AI: It delves into the ethical challenges of AI such as human bias in machine learning, lack of transparency, etc. The topic also explains how to apply the Trusted AI Principles of Salesforce to given scenarios.
Topic 4	Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

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Salesforce Certified AI Associate Exam Sample Questions (Q51-Q56):

NEW QUESTION # 51
What does the term "data completeness" refer to in the context of data quality?

A. The ability to access data from multiple sources in real time
B. The process of aggregating multiple datasets from various databases
C. The degree to which all required data points are present in the dataset

Answer: C

Explanation:
Data completeness is a measure of data quality that assesses whether all required data points are present in a dataset. It checks for missing values or gaps in data necessary for accurate analysis and decision-making. In the context of Salesforce, ensuring data completeness is crucial for the effectiveness of CRM operations, reporting, and AI-driven applications like Salesforce Einstein, which rely on complete data to function optimally. Salesforce provides various tools and features, such as data validation rules and batch data import processes, that help maintain data completeness across its platform. Detailed guidance on managing data quality in Salesforce can be found in the Salesforce Help documentation on data management at Salesforce Help Data Management.

NEW QUESTION # 52
What is one way to achieve transparency in AI?

A. Communicate AI goals and objectives with those involved prior to all interactions.
B. Establish an ethical and unbiased culture amongst those involved.
C. Allow users to give feedback regarding the inferences the AI makes about them.

Answer: C

Explanation:
Transparency in AI refers to making AI decisions understandable and accountable to users and stakeholders.
It involves explaining how AI models make decisions and ensuring that users can question or challenge AI outcomes.
Option A (Incorrect): While establishing an ethical and unbiased culture is essential for responsible AI development, it does not directly contribute to AI transparency. Transparency requires clear communication and user engagement.
Option B (Incorrect): Communicating AI goals and objectives is helpful but insufficient on its own.
Transparency also includes revealing AI decision-making processes and allowing user oversight.
Option C (Correct): Allowing users to give feedback regarding AI inferences ensures transparency by making AI decision-making accountable. Users can report errors, biases, or misunderstandings, helping improve AI fairness and reliability.

NEW QUESTION # 53
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?

A. Test with diverse and representative datasets appropriate for how the model will be used.
B. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
C. Test only with data from a specific region or demographic to limit the risk of data leaks.

Answer: A

Explanation:
Explanation
"Testing with diverse and representative datasets appropriate for how the model will be used aligns with Salesforce's Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences.
Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."

NEW QUESTION # 54
What is the most likely impact that high-quality data will have on customer relationships?

A. Improved customer trust and satisfaction
B. Higher customer acquisition costs
C. Increased brand loyalty

Answer: A

Explanation:
"The most likely impact that high-quality data will have on customer relationships is improved customer trust and satisfaction. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve customer relationships by enabling AI systems to provide personalized and relevant products, services, or solutions that meet the customers' expectations, needs, and interests. High-quality data can also improve customer trust and satisfaction by reducing errors, delays, or waste in customer interactions."

NEW QUESTION # 55
How does AI which CRM help sales representatives better understand previous customer interactions?

A. Provides call summaries
B. Triggers personalized service replies
C. Creates, localizes, and translates product descriptions

Answer: A

Explanation:
Explanation
"Providing call summaries is how AI with CRM helps sales representatives better understand previous customer interactions. Call summaries are a feature that uses natural language processing (NLP) to analyze voice conversations between sales representatives and customers and generate summaries or transcripts of the calls. Call summaries can help sales representatives better understand previous customer interactions by providing key information, insights, or action items from the calls."

NEW QUESTION # 56
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