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Salesforce-AI-Associate Exam
Salesforce.Salesforce-AI-Associate.v2025-12-30.q72 Dumps

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Question 66

What is a potential outcome of using poor-quality data in AI application?

A.AI model training becomes slower and less efficient
B.AI models may produce biased or erroneous results.
C.AI models become more interpretable

Correct Answer: B

Explanation
"A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete,inconsistent, irrelevant, or outdated for the AI task. Poor-quality data 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. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting."

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Question 67

Cloud Kicks uses Einstein to generate predictions but is not seeing accurate results. What is a potential reason for this?

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

Correct Answer: B

AI models rely on high-quality data to produce accurate and reliable predictions. Poor data quality-such as missing values, inconsistent formatting, or biased data-can negatively impact AI performance.
Option A (Incorrect): If Cloud Kicks is using Einstein AI, it is unlikely that they are using the wrong product, as Einstein is designed for predictive analytics. The issue is more likely related to data quality or model training.
Option B (Correct): Poor data quality is one of the most common reasons for inaccurate AI predictions. If the input data contains errors, biases, or incomplete information, the AI model will generate flawed insights.
Regular data cleaning and preprocessing are essential for improving prediction accuracy.
Option C (Incorrect): Having too much data does not necessarily result in inaccurate predictions. In fact, more data can improve model performance if properly structured and cleaned. However, if the data is noisy or unstructured, it may lead to inconsistencies.

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Question 68

What are predictive analytics, machine learning, natural language processing (NLP), and computer vision?

A.Different types of data models used in Salesforce
B.Different types of automation tools used in Salesforce
C.Different types of AI that can be applied in Salesforce

Correct Answer: C

Predictive analytics, machine learning, natural language processing (NLP), and computer vision are all types of artificial intelligence technologies that can be applied in Salesforce to enhance various aspects of business operations and customer interactions. Predictive analytics uses historical data to make predictions about future events. Machine learning involves algorithms that can learn from and make decisions based on data.
NLP is concerned with the interactions between computers and humans using natural language, and computer vision interprets and processes visual information from the world to make sense of it in the way humans do.
Salesforce harnesses these AI technologies, particularly through its Einstein platform, to provide powerful tools that help businesses automate tasks, make better decisions, and offer more personalized services. For more on how Salesforce utilizes these AI technologies, you can explore the Einstein AI services documentation at Salesforce Einstein.

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Question 69

A sales manager wants to improve their processes using AI in Salesforce?
Which application of AI would be most beneficial?

A.Lead soring and opportunity forecasting
B.Sales dashboards and reporting
C.Data modeling and management

Correct Answer: A

"Lead scoring and opportunity forecasting are applications of AI that would be most beneficial for a sales manager who wants to improve their processes using AI in Salesforce. Lead scoring can help prioritize leads based on their likelihood to convert, while opportunity forecasting can help predict future sales or revenue based on historical data and trends. These applications of AI can help optimize sales processes by providing insights and recommendations that can increase sales efficiency and effectiveness."

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Question 70

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

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

Correct Answer: C

"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."

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