Salesforce Salesforce Certifications SALESFORCE-AI-ASSOCIATE Questions & Answers

• Question 71:

  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. Completeness

  B. Accuracy

  C. Consistency

  Correct Answer: C

  "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."

• Question 72:

  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?

  A. Duplication

  B. Usage

  C. Completeness

  Correct Answer: C

  By checking for null values, a business analyst (BA) is verifying the data quality component of completeness. Completeness refers to the absence of missing values or gaps in the data, which is essential for the accuracy and reliability of reports and analytics used in AI models. Null values can indicate incomplete data, which may adversely affect the performance of AI applications by leading to incorrect predictions or insights. Salesforce emphasizes the importance of data completeness for effective data analysis and provides tools for data quality assessment and improvement. Details on handling data completeness in Salesforce can be explored at Salesforce Help Data Management.

• Question 73:

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

  A. Ensures compliance with laws and regulations

  B. Confirms the data is accessible to all users

  C. Increases the volume of data collected

  Correct Answer: A

  "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."

• Question 74:

  What is one technique to mitigate bias and ensure fairness in AI applications?

  A. Ongoing auditing and monitoring of data that is used in AI applications

  B. Excluding data features from the Al application to benefit a population

  C. Using data that contains more examples of minority groups than majority groups

  Correct Answer: A

  A technique to mitigate bias and ensure fairness in AI applications is ongoing auditing and monitoring of the data used in AI applications. Regular audits help identify and address any biases that may exist in the data, ensuring that AI models function fairly and without prejudice. Monitoring involves continuously checking the performance of AI systems to safeguard against discriminatory outcomes. Salesforce emphasizes the importance of ethical AI practices, including transparency and fairness, which can be further explored through Salesforce's AI ethics guidelines at Salesforce AI Ethics.

• Question 75:

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

  Which field type should they use to ensure data quality?

  A. Text

  B. Picklist

  C. Number

  Correct Answer: B

  "A picklist field type should be used to ensure data quality for capturing an order's destination country. A picklist field type allows the user to select one or more predefined values from a list. A picklist field type can ensure data quality by enforcing consistency, accuracy, and completeness of the data values."

• Question 76:

  How does the "right of least privilege" reduce the risk of handling sensitive personal data?

  A. By limiting how many people have access to data

  B. By reducing how many attributes are collected

  C. By applying data retention policies

  Correct Answer: A

  "The "right of least privilege" reduces the risk of handling sensitive personal data by limiting how many people have access to data. The "right of least privilege" is a security principle that states that each user or system should have the minimum level of access or privilege necessary to perform their tasks or functions. The "right of least privilege" can help protect sensitive personal data from unauthorized access, misuse, or leakage."

• Question 77:

  Cloud Kicks wants to use an AI mode to predict the demand for shoes using historical data on sales and regional characteristics.

  What is an essential data quality dimension to achieve this goal?

  A. Reliability

  B. Volume

  C. Age

  Correct Answer: A

  "Reliability is an essential data quality dimension to achieve the goal of predicting the demand for shoes using historical data on sales and regional characteristics. Reliability means that the data values are trustworthy, credible, and authoritative for the AI task. Reliable data can improve the accuracy and confidence of AI predictions, as they reflect the true state or condition of the target population or domain. For example, reliable data can help predict the demand for shoes by using verified and validated sales and regional data."

• Question 78:

  A sales manager wants to use AI to help sales representatives log their calls quicker and more accurately.

  Which functionality provides the best solution?

  A. Call Summaries

  B. Sales Dialer

  C. Auto-Generated Sales Tasks

  Correct Answer: A

  The best functionality to help sales representatives log their calls quicker and more accurately is the use of AI-generated Call Summaries. This feature leverages AI to analyze voice data from sales calls and automatically generate concise summaries and actionable insights, which are then logged into the CRM system. This not only speeds up the process of recording call details but also enhances the accuracy of the data captured, reducing the likelihood of human error and ensuring that important details are not missed. Salesforce provides AI tools that integrate with telephony solutions to enable these capabilities, enhancing the efficiency of sales operations. For more information on Salesforce AI features like Einstein Call Coaching that support this functionality, visit Salesforce Einstein Call Coaching.

• Question 79:

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

  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.

  Correct Answer: B

  "High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve the performance and reliability of AI systems, as they have enough and correct information to learn from and make accurate predictions. High-quality data can also improve the trustworthiness of AI-driven decisions, as users can have more confidence and satisfaction in using AI systems."

• Question 80:

  What is the significance of explainability of trusted AI systems?

  A. Increases the complexity of AI models

  B. Enhances the security and accuracy of AI models

  C. Describes how Al models make decisions

  Correct Answer: C

  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.