RELIABLE SALESFORCE-AI-ASSOCIATE EXAM VOUCHER - THE BEST SALESFORCE SALESFORCE-AI-ASSOCIATE ACTUAL DUMP: SALESFORCE CERTIFIED AI ASSOCIATE EXAM

Reliable Salesforce-AI-Associate Exam Voucher - The Best Salesforce Salesforce-AI-Associate Actual Dump: Salesforce Certified AI Associate Exam

Reliable Salesforce-AI-Associate Exam Voucher - The Best Salesforce Salesforce-AI-Associate Actual Dump: Salesforce Certified AI Associate Exam

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

TopicDetails
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
  • 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 Trusted AI Principles of Salesforce to given scenarios.
Topic 3
  • AI Capabilities in CRM: Get familiar with the benefits of AI and capabilities of CRM.
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 (Q42-Q47):

NEW QUESTION # 42
Cloud Kicks wants to develop a solution to predict customers product interests based on historical data. The company found that employees from one region use a text field to capture the product category, while employees from all other locations use a plckllst.
Which data quality dimension is affected in this scenario?

  • A. Consistency
  • B. Completeness
  • C. Accuracy

Answer: A

Explanation:
Explanation
"Consistency is the data quality dimension that is affected in this scenario. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources.
Inconsistent data can cause confusion, errors, or duplication in data analysis and processing. For example, using different field types for the same attribute can affect the consistency of the data."


NEW QUESTION # 43
What is the significance of explainability of trusted AI systems?

  • A. Increases the complexity of AI models
  • B. Describes how Al models make decisions
  • C. Enhances the security and accuracy of AI models

Answer: B

Explanation:
The significance of the explainability of trusted AI systems is that it describes how AI models make decisions. Explainability is crucial for building trust and accountability in AI systems, ensuring that users and stakeholders understand the decision-making processes and outcomes generated by AI. This is particularly important in scenarios where AI decisions impact personal or financial status, such as in credit scoring or healthcare diagnostics. Salesforce emphasizes the importance of explainable AI through its ethical AI practices, aiming to make AI systems more transparent and understandable. More details about Salesforce's approach to ethical and explainable AI can be found in Salesforce AI ethics resources at Salesforce AI Ethics.


NEW QUESTION # 44
A developer is tasked with selecting a suitable dataset for training an AI model in Salesforce to accurately predict current customer behavior.
What Is a crucial factor that the developer should consider during selection?

  • A. Number of variables ipn the dataset
  • B. Size of the dataset
  • C. Age of the dataset

Answer: B

Explanation:
"The size of the dataset is a crucial factor that the developer should consider during selection. The size of the dataset refers to the amount or volume of data available for training an AI model. The size of the dataset can affect thefeasibility and quality of the AI model, as well as the choice of AI techniques and tools. The size of the dataset should be large enough to provide sufficient information for the AI model to learn from and generalize well to new data."


NEW QUESTION # 45
What are some key benefits of AI in improving customer experiences in CRM?

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

Answer: A

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 # 46
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

Answer: B

Explanation:
"A potential outcome of using poor-quality data inAI 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 reliabilityof 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."


NEW QUESTION # 47
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