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Salesforce-AI-Associate Practice Exam Questions and Answers

Salesforce Certified AI Associate Exam (WI25)

Last Update 1 month ago
Total Questions : 105

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Question # 1

A business analyst (BA) is preparing a new use case for Al. They run a report to check for null values in the attributes they plan to use.

Which data quality component Is the BA verifying by checking for null values?

Options:

A.  

Duplication

B.  

Usage

C.  

Completeness

Discussion 0
Question # 2

What are the three commonly used examples of AI in CRM?

Options:

A.  

Predictive scoring, reporting, Image classification

B.  

Predictive scoring, forecasting, recommendations

C.  

Einstein Bots, face recognition, recommendations

Discussion 0
Question # 3

Cloud Kicks wants to use AI to enhance its sales processes and customer support.

Which capacity should they use?

Options:

A.  

Dashboard of Current Leads and Cases

B.  

Sales path and Automaton Case Escalations

C.  

Einstein Lead Scoring and Case Classification

Discussion 0
Question # 4

Which action introduces bias in the training data used for AI algorithms?

Options:

A.  

Using a large dataset that is computationally expensive

B.  

Using a dataset that represents diverse perspectives and populations

C.  

Using a dataset that underrepresents perspectives and populations

Discussion 0
Question # 5

A Salesforce administrator creates a new field to capture an order's destination country.

Which field type should they use to ensure data quality?

Options:

A.  

Text

B.  

Picklist

C.  

Number

Discussion 0
Question # 6

Cloud Kicks wants to evaluate the quality of its sales data.

Which first step should they take for the data quality assessment?

Options:

A.  

Plan and align territories,

B.  

Run a new report or dashboard.

C.  

Identify business objectives.

Discussion 0
Question # 7

How does data quality impact the trustworthiness of Al-driven decisions?

Options:

A.  

The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.

B.  

High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.

C.  

Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.

Discussion 0
Question # 8

What are some of the ethical challenges associated with AI development?

Options:

A.  

Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes

B.  

Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions

C.  

Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-making

Discussion 0
Question # 9

What is a societal implication of excluding ethics in AI development?

Options:

A.  

Faster and cheaper development

B.  

More innovation and creativity

C.  

Harm to marginalized communities

Discussion 0
Question # 10

What is a potential source of bias in training data for AI models?

Options:

A.  

The data is collected in area time from sources systems.

B.  

The data is skewed toward is particular demographic or source.

C.  

The data is collected from a diverse range of sources and demographics.

Discussion 0
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