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Salesforce Certified AI Associate Exam Sample Questions (Q95-Q100):
NEW QUESTION # 95
Cloud Kicks plans to use automated chat as its primary support channel.
Which Einstein feature should they use?
- A. Discovery
- B. Bots
- C. Next Best Action
Answer: B
Explanation:
For Cloud Kicks, using automated chat as the primary support channel, the recommended Einstein feature is Bots. Einstein Bots are designed to automate customer interactions on common issues through chat and messaging platforms. They can handle routine requests, provide quick answers to frequently asked questions, and escalate more complex issues to human agents. Using Einstein Bots helps improve customer service efficiency and speed, leading to enhanced customer satisfaction. To learn more about setting up and optimizing Einstein Bots for a business, you can visit the Salesforce documentation on Einstein Bots at Salesforce Einstein Bots.
NEW QUESTION # 96
What should be done to prevent bias from entering an AI system when training it?
- A. Include Proxy variables.
- B. Import diverse training data.
- C. Use alternative assumptions.
Answer: B
Explanation:
Explanation
"Using diverse training data is what should be done to prevent bias from entering an AI system when training it. Diverse training data means that the data covers a wide range of features andpatterns that are relevant for the AI task. Diverse training data can help prevent bias by ensuring that the AI system learns from a balanced and representative sample of the target population or domain. Diverse training data can also help improve the accuracy and generalization of the AI system by capturing more variations and scenarios in the data."
NEW QUESTION # 97
Which type of AI can enhance customer service agents' email responses by analyzing the written content of previous emails?
- A. Machine learning
- B. Natural language processing
- C. Deep learning
Answer: B
Explanation:
Natural language processing (NLP) is the type of AI that can enhance customer service agents' email responses by analyzing the written content of previous emails. NLP technologies interpret and generate human language, allowing AI systems to understand, respond to, and even anticipate customer needs based on email interactions. This capability helps in crafting more relevant, accurate, and personalized email responses, improving customer service quality. Salesforce utilizes NLP in its Einstein AI platform to augment various customer service functions. More about Salesforce Einstein's NLP capabilities can be found on the Salesforce Einstein page at Salesforce Einstein NLP.
NEW QUESTION # 98
How does a data quality assessment impact business outcome for companies using AI?
- A. Improves the speed of AI recommendations
- B. Provides a benchmark for AI predictions
- C. Accelerates the delivery of new AI solutions
Answer: B
Explanation:
Explanation
"A data quality assessment impacts business outcomes for companies using AI by providing a benchmark for AI predictions. A data quality assessment is a process that measures and evaluates the quality of data for a specific purpose or task. A data quality assessment can help identify and address any issues or gaps in the data quality dimensions, such as accuracy, completeness, consistency, relevance, and timeliness. A data quality assessment can impact business outcomes for companies using AI by providing a benchmark for AI predictions, as it can help ensure that the predictions are based on high-quality data that reflects the true state or condition of the target population or domain."
NEW QUESTION # 99
Cloud Kicks discovered multiple variations of state and country values in contact records.
Which data quality dimension is affected by this issue?
- A. Usage
- B. Consistency
- C. Accuracy
Answer: B
Explanation:
"Consistency is the data quality dimensionthat is affected by multiple variations of state and country values in contact records. 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."
NEW QUESTION # 100
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