VALID SALESFORCE-AI-ASSOCIATE STUDY PLAN & SALESFORCE-AI-ASSOCIATE SAMPLE QUESTIONS ANSWERS

Valid Salesforce-AI-Associate Study Plan & Salesforce-AI-Associate Sample Questions Answers

Valid Salesforce-AI-Associate Study Plan & Salesforce-AI-Associate Sample Questions Answers

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Salesforce Certified AI Associate Exam Sample Questions (Q13-Q18):

NEW QUESTION # 13
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. Auto-Generated Sales Tasks
  • B. Call Summaries
  • C. Sales Dialer

Answer: B

Explanation:
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.


NEW QUESTION # 14
How does AI assist in lead qualification?

  • A. Scores leads based on customer data
  • B. Creates personalized SMS campaigns
  • C. Automatically interacts with prospects

Answer: A

Explanation:
AI assists in lead qualification primarily by scoring leads based on customer data. This process, known as lead scoring, uses machine learning algorithms to evaluate leads against a set of predefined criteria that reflect potential interest and sales readiness. The scores assigned help sales teams prioritize their efforts toward leads most likely to convert, thus improving efficiency and success rates in sales activities. Salesforce AI enhances this process through features like Einstein Lead Scoring, which automatically calculates scores based on both historical conversion data and behavioral data from prospects. For further insights, Salesforce provides detailed documentation on lead scoring with AI at Salesforce Einstein Lead Scoring.


NEW QUESTION # 15
What is a possible outcome of poor data quality?

  • A. Biases in data can be inadvertently learned and amplified by AI systems.
  • B. AI predictions become more focused and less robust.
  • C. AI models maintain accuracy but have slower response times.

Answer: A

Explanation:
"A possible outcome of poor data quality is that biases in data can be inadvertently learned and amplified by AI systems. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI systems, as they may not have enough or correct information to learn from or make accurate predictions. Poor data quality can also introduce or exacerbate biases in data, such as human bias, societal bias, or confirmation bias, which can affect the fairness and ethics of AI systems."


NEW QUESTION # 16
What is the best method to safeguard customer data privacy?

  • A. Archive customer data on a recurring schedule.
  • B. Track customer data consent preferences.
  • C. Automatically anonymize all customer data.

Answer: B

Explanation:
"Tracking customer data consent preferences is the best method to safeguard customer data privacy. Data privacy is the right of individuals to control how their personal data is collected, used, shared, or stored by others. Tracking customer data consent preferences means respecting and honoring the choices and preferencesof customers regarding their personal data. Tracking customer data consent preferences can help ensure compliance with data privacy laws and regulations, as well as build trust and loyalty with customers."


NEW QUESTION # 17
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?

  • A. Poor data quality
  • B. Too much data
  • C. The wrong product

Answer: A

Explanation:
Explanation
"Poor data quality is a potential reason for not seeing accurate results from an AI model. Poor data quality means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor data quality can affect the performance and reliability of AI models, as they may not have enough or correct information to learn from or make accurate predictions."


NEW QUESTION # 18
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