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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:
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NEW QUESTION # 21
Why is it critical to consider privacy concerns when dealing with AI and CRM data?
- A. Ensures compliance with laws and regulations
- B. Increases the volume of data collected
- C. Confirms the data is accessible to all users
Answer: A
Explanation:
Explanation
"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."
NEW QUESTION # 22
A business analyst (BA) wants to improve business by enhancing their sales processes and customer..
Which AI application should the BA use to meet their needs?
- A. Lead scoring, opportunity forecasting, and case classification
- B. Machine learning models and chatbot predictions
- C. Sales data cleansing and customer support data governance
Answer: A
Explanation:
Explanation
"Lead scoring, opportunity forecasting, and case classification are AI applications that can help a business analyst improve their sales processes and customer support. Lead scoring can help prioritize leads based on their likelihood to convert, opportunity forecasting can help predict future sales or revenue based on historical data and trends, and case classification can help categorize and route cases based on their attributes."
NEW QUESTION # 23
What is a key challenge of human AI collaboration in decision-making?
- A. Leads to move informed and balanced decision-making
- B. Creates a reliance on AI, potentially leading to less critical thinking and oversight
- C. Reduce the need for human involvement in decision-making processes
Answer: B
Explanation:
Explanation
"A key challenge of human-AI collaboration in decision-making is that it creates a reliance on AI, potentially leading to less critical thinking and oversight. Human-AI collaboration is a process that involves humans and AI systems working together to achieve a common goal or task. Human-AI collaboration can have many benefits, such as leveraging the strengths and complementing the weaknesses of both humans and AI systems.
However, human-AI collaboration can also pose some challenges, such as creating a reliance on AI, potentially leading to less critical thinking and oversight. For example, human-AI collaboration can create a reliance on AI if humans blindly trust or follow the AI recommendations without questioning or verifying their validity or rationale."
NEW QUESTION # 24
A customer using Einstein Prediction Builder is confused about why a certain prediction was made.
Following Salesforce's Trusted AI Principle of Transparency, which customer information should be accessible on the Salesforce Platform?
- A. An explanation of the prediction's rationale and a model card that describes how the model was created
- B. An explanation of how Prediction Builder works and a link to Salesforce's Trusted AI Principles
- C. A marketing article of the product that clearly outlines the oroduct's capabilities and features
Answer: A
Explanation:
Explanation
"An explanation of the prediction's rationale and a model card that describes how the model was created should be accessible on the Salesforce Platform following Salesforce's Trusted AI Principle of Transparency.
Transparency means that AI systems should be designed and developed with respect for clarity and openness in how they work and why they make certain decisions. Transparency also means that AI users should be able to access relevant information and documentation about the AI systems they interact with."
NEW QUESTION # 25
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
- A. Engagement
- B. Demographic
- C. Transactional
Answer: B
Explanation:
Explanation
"Demographic data should be omitted to avoid introducing unintended bias to an AI model. Demographic data is data that describes the characteristics of a population or a group of people, such as age, gender, race, ethnicity, income, education, or occupation. Demographic data can lead to bias if it is used to discriminate or treat people differently based on their identity or attributes. Demographic data can also reflect existing biases or stereotypes in society or culture, which can affect the fairness and ethics of AI systems."
NEW QUESTION # 26
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:
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 preferences of 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 # 27
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
- A. Inclusivity
- B. Transparency
- C. Accountability
Answer: A
Explanation:
Explanation
"Conducting a series of Consequence Scanning workshops to support testing diverse datasets is an action that practices Salesforce's Trusted AI Principle of Inclusivity. Inclusivity is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Conducting Consequence Scanning workshops means engaging with various stakeholders to identify and assess the potential impacts and implications of AI systems on different groups or domains. Conducting Consequence Scanning workshops can help practice Inclusivity by ensuring that diverse datasets are used to test and evaluate AI systems."
NEW QUESTION # 28
Cloud Kicks wants to implement AI features on its 5aiesforce Platform but has concerns about potential ethical and privacy challenges.
What should they consider doing to minimize potential AI bias?
- A. Integrate AI models that auto-correct biased data.
- B. Use demographic data to identify minority groups.
- C. Implement Salesforce's Trusted AI Principles.
Answer: C
Explanation:
Explanation
"Implementing Salesforce's Trusted AI Principles is what Cloud Kicks should consider doing to minimize potential AI bias. Salesforce's Trusted AI Principles are a set of guidelines and best practices for developing and using AI systems in a responsible and ethical way. The principles include Accountability, Fairness & Equality, Transparency & Explainability, Privacy & Security, Reliability & Safety, Inclusivity & Diversity, Empowerment & Education."
NEW QUESTION # 29
What are some key benefits of AI in improving customer experiences in CRM?
- A. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
- B. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats
- C. Fully automates the customer service experience, ensuring seamless automated interactions with customers
Answer: A
Explanation:
Explanation
"Streamlining case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions are some key benefits of AI in improving customer experiences in CRM. AI can help automate and optimize various aspects of customer service, such as routing cases to the right agents, providing relevant information or suggestions, and generating reports or insights. AI can also help enhance customer satisfaction and loyalty by reducing wait times, improving response quality, and providing personalized solutions."
NEW QUESTION # 30
What is the most likely impact that high-quality data will have on customer relationships?
- A. Higher customer acquisition costs
- B. Increased brand loyalty
- C. Improved customer trust and satisfaction
Answer: C
Explanation:
Explanation
"The most likely impact that high-quality data will have on customer relationships is improved customer trust and satisfaction. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve customer relationships by enabling AI systems to provide personalized and relevant products, services, or solutions that meet the customers' expectations, needs, and interests. High-quality data can also improve customer trust and satisfaction by reducing errors, delays, or waste in customer interactions."
NEW QUESTION # 31
What is the key difference between generative and predictive AI?
- A. Generative AI finds content similar to existing data and predictive AI analyzes existing data.
- B. Generative AI analyzes existing data and predictive AI creates new content based on existing data.
- C. Generative AI creates new content based on existing data and predictive AI analyzes existing data.
Answer: C
Explanation:
Explanation
"The key difference between generative and predictive AI is that generative AI creates new content based on existing data and predictive AI analyzes existing data. Generative AI is a type of AI that can generate novel content such as images, text, music, or video based on existing data or inputs. Predictive AI is a type of AI that can analyze existing data or inputs and make predictions or recommendations based on patterns or trends."
NEW QUESTION # 32
Which best describes the different between predictive AI and generative AI?
- A. Predictive new and original output for a given input.
- B. Predictive AI uses machine learning to classes or predict output from its input data whereas generative AI does not use machine learning to generate its output
- C. Predictive AI and generative have the same capabilities differ in the type of input they receive:
predictive AI receives raw data whereas generation AI receives natural language.
Answer: A
Explanation:
Explanation
"The difference between predictive AI and generative AI is that predictive AI analyzes existing data to make predictions or recommendations based on patterns or trends, while generative AI creates new content based on existing data or inputs. Predictive AI is a type of AI that uses machine learning techniques to learn from existing data and make predictions or recommendations based on the data. For example, predictive AI can be used to forecast sales, revenue, or demand based on historical data and trends. Generative AI is a type of AI that uses machine learning techniques togenerate novel content such as images, text, music, or video based on existing data or inputs. For example, generative AI can be used to create realistic faces, write summaries, compose songs, or produce videos."
NEW QUESTION # 33
How does AI which CRM help sales representatives better understand previous customer interactions?
- A. Creates, localizes, and translates product descriptions
- B. Provides call summaries
- C. Triggers personalized service replies
Answer: B
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 # 34
Which Einstein capability uses emails to create content for Knowledge articles?
- A. Predict
- B. Discover
- C. Generate
Answer: C
Explanation:
Explanation
"Einstein Generate uses emails to create content for Knowledge articles. Einstein Generate is a natural language generation (NLG) feature that can automatically write summaries, descriptions, or recommendations based on data or text inputs. For example, Einstein Generate can analyze email conversations between agents and customers and generate draft articles for the Knowledge base."
NEW QUESTION # 35
Cloud Kicks wants to use Einstein Prediction Builder to determine a customer's likelihood of buying specific products; however, data quality is a...
How can data quality be assessed quality?
- A. Build reports to expire the data quality.
- B. Leverage data quality apps from AppExchange
- C. Build a Data Management Strategy.
Answer: B
Explanation:
Explanation
"Leveraging data quality apps from AppExchange is how data quality can be assessed. Data quality is the degree to which data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can affect the performance and reliability of AI systems, as they depend on the quality of the data they use to learn from and make predictions. Leveraging data quality apps from AppExchange means using third-party applications or solutions that can help measure, monitor, or improve data quality in Salesforce."
NEW QUESTION # 36
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
- B. Opportunity List View, Lead List View, Account List view
- C. Opportunity Scoring, Lead Scoring, Account Insights
Answer: C
Explanation:
Explanation
"Opportunity Scoring, Lead Scoring, Account Insights are features of Einstein that enhance sales efficiency and effectiveness. Opportunity Scoring and Lead Scoring use predictive models to assign scores to opportunities and leads based on their likelihood to close or convert. Account Insights use natural language processing (NLP) to provide relevant news and insights about accounts based on their industry, location, or events."
NEW QUESTION # 37
An administrator at Cloud Kicks wants to ensure that a field is set up on the customer record so their preferred name can be captured.
Which Salesforce field type should the administrator use to accomplish this?
- A. Rich Text Area
- B. Multi-Select Picklist
- C. Text
Answer: C
Explanation:
Explanation
"A text field type should be used to capture the customer's preferred name. A text field type allows the user to enter any combination of letters, numbers, or symbols. A text field type can be used to store names, addresses, phone numbers, or other personal information."
NEW QUESTION # 38
What is a possible outcome of poor data quality?
- A. AI models maintain accuracy but have slower response times.
- B. Biases in data can be inadvertently learned and amplified by AI systems.
- C. AI predictions become more focused and less robust.
Answer: B
Explanation:
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 # 39
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
- A. Working with human rights experts
- B. Striving for model explain ability
- C. Testing models with diverse datasets
Answer: C
Explanation:
Explanation
"An example of Salesforce's Trusted AI Principle of Inclusivity in practice is testing models with diverse datasets. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing modelswith diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."
NEW QUESTION # 40
Cloud Kicks implements a new product recommendation feature for its shoppers that recommends shoes of a given color to display to customers based on the color of the products from their purchase history.
Which type of bias is most likely to be encountered in this scenario?
- A. Societal
- B. Confirmation
- C. Survivorship
Answer: B
Explanation:
Explanation
"Confirmation bias is most likely to be encountered in this scenario. Confirmation bias is a type of bias that occurs when data or information confirms or supports one's existing beliefs or expectations. For example, confirmation bias can occur when a product recommendation feature only recommends shoes of a given color based on the customer's purchase history, without considering other factors or preferences that may influence their choice."
NEW QUESTION # 41
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
- A. Chances of bias are remove
- B. Chances of bIas and mitigated
- C. Chances of bias are aggravated
Answer: B
Explanation:
Explanation
"Data quality and transparency can help mitigate the chances of bias in generative AI. Data quality means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Data quality can help mitigate bias by ensuring that the generative AI model learns from a balanced and representative sample of the target population or domain. Data transparency means that the data sources, methods, and processes are clear and open to inspection and verification. Data transparency can help mitigate bias by allowing users to understand and evaluate the data used or generated by the generative AI model."
NEW QUESTION # 42
A data quality expert at Cloud Kicks want to ensure that each new contact contains at least an email address ...
Which feature should they use to accomplish this?
- A. Duplicate matching rule
- B. Validation rule
- C. Autofill
Answer: B
Explanation:
Explanation
"A validation rule should be used to ensure that each new contact contains at least an email address or phone number. A validation rule is a feature that checks the data entered by users for errors before saving it to Salesforce. A validation rule can help ensure data quality by enforcing certain criteria or conditions for the data values."
NEW QUESTION # 43
Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results?
What to a potential mason for this?
- A. Too much data
- B. The wrong product
- C. Poor data quality
Answer: C
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 # 44
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