Salesforce Certified AI Associate Question Set 1

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More Question sets for Salesforce Certified Associate: Salesforce Certified AI Associate Question Sets

Number of Questions in this Set: 20

Q.1 What is the most likely impact that high-quality data will have on customer relationships?

  1. Improved customer trust and satisfaction
  2. Increased brand loyalty
  3. Higher customer acquisition costs
Answer

A. Improved customer trust and satisfaction

Q.2 What are the key components of the data quality standard?

  1. Accuracy, Completeness, Consistency
  2. Reviewing, Updating, Archiving
  3. Naming, Formatting, Monitoring
Answer

A. Accuracy, Completeness, Consistency

Q.3 Cloud Kicks wants to use Einstein Prediction Builder to determine a customer’s likelihood of buying specific products; however, data quality is a concern.
How can data quality be assessed quickly?

  1. Build a Data Management Strategy.
  2. Build reports to expire the data quality.
  3. Leverage data quality apps from AppExchange
Answer

C. Leverage data quality apps from AppExchange

Q.4 A data quality expert at Cloud Kicks want to ensure that each new contact contains at least an email address or phone number.

Which feature should they use to accomplish this?

  1. Autofill
  2. Duplicate matching rule
  3. Validation rule
Answer

C. Validation rule

Q.5 What role does data quality play in the ethical use of AI applications?

  1. High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination.
  2. Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups.
  3. High-quality data ensures the presence of demographic attributes required for personalized campaigns.
Answer

A. High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination.

Q.6 What is a key challenge of human-AI collaboration in decision-making?

  1. Leads to more informed and balanced decision-making.
  2. Creates a reliance on AI, potentially leading to less critical thinking and oversight.
  3. Reduce the need for human involvement in decision-making processes.
Answer

B. Creates a reliance on AI, potentially leading to less critical thinking and oversight

Q.7 Which statement exemplifies Salesforce’s honesty guideline when training AI models?

  1. Control bias, toxicity, and harmful content with embedded guardrails and guidance.
  2. Ensure appropriate consent and transparency when using AI- generated responses.
  3. Minimize the AI model’s carbon footprint and environmental impact during training.
Answer

B. Ensure appropriate consent and transparency when using AI- generated responses.

Q.8 What should be done to prevent bias from entering an AI system when training it?

  1. Import diverse training data.
  2. Use alternative assumptions.
  3. Include proxy variables.
Answer

A. Import diverse training data.

Q.9 How does AI within CRM help sales representatives better understand previous customer interactions?

  1. Creates, localizes, and translates product descriptions.
  2. Provides call summaries.
  3. Triggers personalized service replies.
Answer

B. Provides call summaries.

Q.10 A business analyst (BA) wants to improve business by enhancing their sales processes and customer support.
Which AI applications should the BA use to meet their needs?

  1. Sales data cleansing and customer support data governance.
  2. Machine learning models and chatbot predictions.
  3. Lead scoring, opportunity forecasting, and case classification.
Answer

C. Lead scoring, opportunity forecasting, and case classification.

Q.11 What is an example of ethical debt?

  1. Violating a data privacy law and failing to pay fines.
  2. Delaying an AI product launch to retrain an AI data model.
  3. Launching an AI feature after discovering a harmful bias.
Answer

C. Launching an AI feature after discovering a harmful bias.

Q.12 What is a key consideration regarding data quality in AI implementation?

  1. Techniques from customizing AI features in Salesforce.
  2. Data’s role in training and fine-tuning Salesforce AI models.
  3. Integration process of AI models with Salesforce workflows.
Answer

B. Data’s role in training and fine-tuning Salesforce AI models.

Q.13 What is a potential source of bias in training data for AI models?

  1. A. The data is collected in real time from source systems.
  2. B. The data is collected from a diverse range of sources and demographics.
  3. C. The data is skewed toward a particular demographic or source.
Answer

C. The data is skewed toward a particular demographic or source.

Q.14 Which type of bias imposes a system’s values on others?

  1. Association.
  2. Automation.
  3. Societal.
Answer

B. Automation.

Q.15 A sales manager wants to improve their processes using AI in Salesforce.
Which application of AI would be most beneficial?

  1. Lead scoring and opportunity forecasting.
  2. Data modelling and management.
  3. Sales dashboards and reporting.
Answer

A. Lead scoring and opportunity forecasting.

Q.16 What is the role of Salesforce’s Trusted AI Principles in the context of CRM systems?

  1. Outlining the technical specifications for AI integration.
  2. Providing a framework for AI data model accuracy.
  3. Guiding ethical and responsible use of AI.
Answer

C. Guiding ethical and responsible use of AI.

Q.17 What is machine learning?

  1. A data model used in Salesforce.
  2. AI that can grow its intelligence.
  3. AI that creates new content.
Answer

B. AI that can grow its intelligence.

Q.18 Which best describes the difference between predictive AI and generative AI?

  1. Predictive AI and generative AI have the same capabilities but differ in the type of input they receive; predictive AI receives raw data whereas generative AI receives natural language.
  2. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI does not use machine learning to generate its output.
  3. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine leaning to generate new and original output for a given input.
Answer

C. Predictive AI uses machine learning to classify or predict outputs from its input data whereas generative AI uses machine leaning to generate new and original output for a given input.

Q.19 What is a benefit of data quality and transparency as it pertains to bias in generative AI?

  1. Chances of bias are aggravated.
  2. Chances of bias are removed.
  3. Chances of bias are mitigated.
Answer

C. Chances of bias are mitigated.

Q.20 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 picklist.
Which dimension of data quality is affected in this scenario?

  1. Accuracy.
  2. Completeness.
  3. Consistency.
Answer

C. Consistency.

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