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Valid Salesforce Salesforce-AI-Associate Exam Voucher | Salesforce-AI-Associate Valid Exam Prep

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Salesforce Certified AI Associate Exam Sample Questions (Q62-Q67):

NEW QUESTION # 62
What are the potential consequences of an organization suffering from poor data quality?

A. Low employee morale, stock devaluation, and inability to attract top talent
B. Revenue loss, poor customer service, and reputational damage
C. Technical debt, monolithic system architecture, and slow ETL throughput

Answer: B

Explanation:
The potential consequences of an organization suffering from poor data quality include revenue loss, poor customer service, and reputational damage. Poor data quality can lead to inaccurate analytics and decision- making, impacting customer interactions, marketing strategies, and financial forecasting. These issues ultimately affect customer satisfaction and could lead to financial losses and a damaged brand reputation.
Salesforce highlights the importance of maintaining high data quality for effective CRM and AI applications, offering various tools and best practices to enhance data integrity. For guidance on managing and improving data quality in Salesforce, see the Salesforce documentation on data quality at Salesforce Data Quality.

NEW QUESTION # 63
Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters a recurring Issue of Incomplete customer records, withmissing contact Information and incomplete purchase histories.
How will this incomplete data quality impact the company's operations?

A. The accuracy of product recommendations is hindered.
B. The diversity of product recommendations Is Improved.
C. The response time for product recommendations is stalled.

Answer: A

Explanation:
"The incomplete data quality will impact the company's operations by hindering the accuracy of product recommendations. Incomplete data means that the data is missing some values or attributes that are relevant for the AI task. Incomplete data can affect the performance and reliability of AI models, as they may not have enough information to learn from or make accurate predictions. For example, incomplete customer records can affect the quality of product recommendations, as the AI model may not be able to capture the customers' preferences, behavior, or needs."

NEW QUESTION # 64
What is the significance of explainability of trusted AI systems?

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

Answer: A

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 # 65
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. An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
B. An explanation of the prediction's rationale and a model card that describes how the model was created
C. A marketing article of the product that clearly outlines the oroduct's capabilities and features

Answer: B

NEW QUESTION # 66
Cloud Kicks wants to implement AI features on its 5aiesforce Platform but has concerns about potential ethical and privacy challenges.
What should they consider doing to minimize potential AI bias?

A. Implement Salesforce's Trusted AI Principles.
B. Use demographic data to identify minority groups.
C. Integrate AI models that auto-correct biased data.

Answer: A

Explanation:
"Implementing Salesforce's Trusted AI Principles is what Cloud Kicks should consider doing to minimize potential AI bias. Salesforce's Trusted AI Principles are a set of guidelines and best practices for developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education."

NEW QUESTION # 67
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