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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:
Topic
Details
Topic 1
- 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 the Trusted AI Principles of Salesforce to given scenarios.
Topic 2
- Data for AI: Questions about the importance of data quality and different elements or components of data quality are related to this topic.
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.
Salesforce Certified AI Associate Exam Sample Questions (Q18-Q23):
NEW QUESTION # 18
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records.
Which type of records negatively impact data quality?
- A. Structured
- B. Complete
- C. Duplicate
Answer: C
Explanation:
Duplicate records negatively impact data quality by creating inconsistencies and confusion in database management, leading to potential errors in customer relationship management (CRM) systems like Salesforce. Duplicates can skew analytics results, lead to inefficiencies in customer service, and result in redundant marketing efforts. Salesforce offers various tools to identify and merge duplicate records, thereby maintaining high data integrity. More about managing duplicate records in Salesforce and ensuring data quality can be found in Salesforce's documentation on duplicate management at Salesforce Duplicate Management.
NEW QUESTION # 19
What is an example of ethical debt?
- A. Delaying an AI product launch to retrain an AI data model
- B. Violating a data privacy law and falling to pay fines
- C. Launching an AI feature after discovering a harmful bias
Answer: C
Explanation:
Explanation
"Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical debt is a term that describes the potential harm or risk caused by unethical or irresponsible decisions or actions related to AI systems. Ethical debt can accumulate over time and have negative consequences for users, customers, partners, or society. For example, launching an AI feature after discovering a harmful bias can create ethical debt by exposing users to unfair or inaccurate results that may affect their trust, satisfaction, or well-being."
NEW QUESTION # 20
How does a data quality assessment impact business outcome for companies using AI?
- A. Improves the speed of AI recommendations
- B. Accelerates the delivery of new AI solutions
- C. Provides a benchmark for AI predictions
Answer: C
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 # 21
How does AI which CRM help sales representatives better understand previous customer interactions?
- A. Provides call summaries
- B. Triggers personalized service replies
- C. Creates, localizes, and translates product descriptions
Answer: A
Explanation:
Explanation
"Providing call summaries is how AI with CRM helps sales representatives better understand previous customer interactions. Call summaries are a feature that uses natural language processing (NLP) to analyze voice conversations between sales representatives and customers and generate summaries or transcripts of the calls. Call summaries can help sales representatives better understand previous customer interactions by providing key information, insights, or action items from the calls."
NEW QUESTION # 22
How does a data quality assessment impact business outcome for companies using AI?
- A. Improves the speed of AI recommendations
- B. Accelerates the delivery of new AI solutions
- C. Provides a benchmark for AI predictions
Answer: C
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 AIpredictions, 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 # 23
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