Fantastic Salesforce-AI-Associate Valid Exam Dumps - Pass Salesforce-AI-Associate Exam

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic	Details
Topic 1	Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.
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	AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.

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Salesforce Certified AI Associate Exam Sample Questions (Q33-Q38):

NEW QUESTION # 33
What are the key components of the data quality standard?

A. Naming, formatting, Monitoring
B. Accuracy, Completeness, Consistency
C. Reviewing, Updating, Archiving

Answer: B

Explanation:
"Accuracy, Completeness, Consistency are the key components of the data quality standard. Data quality standard is a set of criteria or measures that define and evaluate the quality of data for a specific purpose or task. Data quality standard can vary by industry, domain, or application, but some common components are accuracy, completeness, and consistency. Accuracy means that the data values are correct andvalid for the data attribute. Completeness means that the data values are not missing any relevant information for the data attribute. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources."

NEW QUESTION # 34
Cloud Kicks wants to optimize its business operations by incorporating AI into its CRM.
What should the company do first to prepare its data for use with AI?

A. Remove biased data.
B. Determine data outcomes.
C. Determine data availability.

Answer: C

Explanation:
Explanation
Before using AI to optimize business operations, the company should first assess the availability and quality of its data. Data is the fuel for AI, and without sufficient and relevant data, AI cannot produce accurate and reliable results. Therefore, the company should identify what data it has, where it is stored, how it is accessed, and how it is maintained. This will help the company understand the feasibility and scope of its AI projects.

NEW QUESTION # 35
Which best describes the different between predictive AI and generative AI?

A. Predictive AI uses machine learning to classes or predict output from its input data whereas generative AI does not use machine learning to generate its output
B. Predictive new and original output for a given input.
C. Predictive AI and generative have the same capabilities differ in the type of input theyreceive: predictive AI receives raw data whereas generation AI receives natural language.

Answer: B

Explanation:
"The difference between predictive AI and generative AI is that predictive AI analyzes existing data to make predictions or recommendations based on patterns or trends, while generative AI creates new content based on existing data or inputs. Predictive AI is a type of AI that uses machine learning techniques to learn from existing data and make predictions or recommendations based on the data. For example, predictive AI can be used to forecast sales, revenue, or demand based on historical data and trends. Generative AI is a type of AI that uses machine learning techniques to generate novel content such as images, text, music, or video based on existing data or inputs. For example, generative AI can be used to create realistic faces, write summaries, compose songs, or produce videos."

NEW QUESTION # 36
Which Einstein capability uses emails to create content for Knowledge articles?

A. Predict
B. Generate
C. Discover

Answer: B

Explanation:
"Einstein Generate uses emails to create content for Knowledge articles. Einstein Generate is a natural language generation (NLG) feature that can automatically write summaries, descriptions, or recommendations based on data or text inputs. For example, Einstein Generate can analyze email conversations between agents and customers and generate draft articles for the Knowledge base."

NEW QUESTION # 37
Why is it critical to consider privacy concerns when dealing with AI and CRM data?

A. Increases the volume of data collected
B. Ensures compliance with laws and regulations
C. Confirms the data is accessible to all users

Answer: B

Explanation:
Explanation
"It is critical to consider privacy concerns when dealing with AI and CRM data because it ensures compliance with laws and regulations. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Data privacy laws and regulations are legal frameworks that define and enforce the rights and obligations of data subjects, data controllers, and data processors regarding personal data. Data privacy laws and regulations vary by country, region, or industry, and may impose different requirements or restrictions on how AI and CRM data can be handled."

NEW QUESTION # 38
......

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Fantastic Salesforce-AI-Associate Valid Exam Dumps - Pass Salesforce-AI-Associate Exam

Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Salesforce Salesforce-AI-Associate Preparation Materials Available In Different Formats

Salesforce Certified AI Associate Exam Sample Questions (Q33-Q38):

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