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Practice Test Salesforce Salesforce-AI-Associate Pdf, Salesforce-AI-Associate Relevant Answers

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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

Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.

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

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.

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Salesforce Certified AI Associate Exam Sample Questions (Q106-Q111):

NEW QUESTION # 106
A customer using Einstein Prediction Builder is confused about why a certain prediction was made.
Following Salesforce's Trusted AI Principle of Transparency, which customer information should be accessible on the Salesforce Platform?

A. A marketing article of the product that clearly outlines the oroduct's capabilities and features
B. An explanation of the prediction's rationale and a model card that describes how the model was created
C. An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles

Answer: B

NEW QUESTION # 107
What are some key benefits of AI in improving customer experiences in CRM?

A. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
B. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
C. Fully automates the customer service experience, ensuring seamless automated interactions with customers

Answer: B

Explanation:
Explanation
"Streamlining case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions are some key benefits of AI in improving customer experiences in CRM. AI can help automate and optimize various aspects of customer service, such as routing cases to the right agents, providing relevant information or suggestions, and generating reports or insights. AI can also help enhance customer satisfaction and loyalty by reducing wait times, improving response quality, and providing personalized solutions."

NEW QUESTION # 108
How is natural language processing (NLP) used in the context of AI capabilities?

A. To understand and generate human language
B. To interpret and understand programminglanguage
C. To cleanse and prepare data for AI implementations

Answer: A

Explanation:
"Natural language processing (NLP) is used in the context of AI capabilities to understand and generate human language. NLP can enable AI systems to interact with humans using natural language, such as speech or text. NLP can also enable AI systems to analyze and extract information from natural language data, such as documents, emails, or social media posts."

NEW QUESTION # 109
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?

A. Poor data quality
B. Too much data
C. The wrong product

Answer: A

Explanation:
Explanation
"Poor data quality is a potential reason for not seeing accurate results from an AI model. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI models, as they may not have enough or correct information to learn from or make accurate predictions."

NEW QUESTION # 110
What is the key difference between generative and predictive AI?

A. Generative AI creates new content based on existing data and predictive AI analyzes existing data.
B. Generative AI finds content similar to existing data and predictive AI analyzes existing data.
C. Generative AI analyzes existing data and predictive AI creates new content based on existing data.

Answer: A

Explanation:
Explanation
"The key difference between generative and predictive AI is that generative AI creates new content based on existing data and predictive AI analyzes existing data. Generative AI is a type of AI that can generate novel content such as images, text, music, or video based on existing data or inputs. Predictive AI is a type of AI that can analyze existing data or inputs and make predictions or recommendations based on patterns or trends."

NEW QUESTION # 111
......

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Lucas White Lucas White

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