2025 Latest Salesforce Salesforce-AI-Associate Real Exam Dumps PDF
Salesforce-AI-Associate Exam Dumps, Salesforce-AI-Associate Practice Test Questions
Salesforce Salesforce-AI-Associate Exam Syllabus Topics:
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NEW QUESTION # 58
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. Survivorship
- B. Societal
- C. Confirmation
Answer: C
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'sexisting 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 # 59
What is a societal implication of excluding ethics in AI development?
- A. Faster and cheaper development
- B. More innovation and creativity
- C. Harm to marginalized communities
Answer: C
Explanation:
Excluding ethics in AI development can lead to societal implications such as harm to marginalized communities. When ethical considerations are not integrated into AI development, the resulting technologies may perpetuate or amplify biases, leading to unfair treatment or discrimination against certain groups. This can reinforce existing social inequalities and prevent these communities from benefiting equally from the advancements in AI technology. Salesforce is committed to responsible AI development and emphasizes the importance of ethical considerations in their development practices to prevent such outcomes. Details on Salesforce's approach to ethical AI and its importance can be found at Salesforce Ethical AI.
NEW QUESTION # 60
Cloud Kicks uses Einstein to generate predictions but is not seeing accurate results. What is a potential reason for this?
- A. Too much data
- B. The wrong product
- C. Poor data quality
Answer: C
Explanation:
AI models rely on high-quality data to produce accurate and reliable predictions. Poor data quality-such as missing values, inconsistent formatting, or biased data-can negatively impact AI performance.
Option A (Incorrect): If Cloud Kicks is using Einstein AI, it is unlikely that they are using the wrong product, as Einstein is designed for predictive analytics. The issue is more likely related to data quality or model training.
Option B (Correct): Poor data quality is one of the most common reasons for inaccurate AI predictions. If the input data contains errors, biases, or incomplete information, the AI model will generate flawed insights.
Regular data cleaning and preprocessing are essential for improving prediction accuracy.
Option C (Incorrect): Having too much data does not necessarily result in inaccurate predictions. In fact, more data can improve model performance if properly structured and cleaned. However, if the data is noisy or unstructured, it may lead to inconsistencies.
NEW QUESTION # 61
Cloud Kicks is testing a new AI model.
Which approach aligns with Salesforce's Trusted AI Principle of Incluslvity?
- A. Test only with data from a specific region or demographic to limit the risk of data leaks.
- B. Rely on a development team with uniform backgrounds to assess the potential societal implications of the model.
- C. Test with diverse and representative datasets appropriate for how the model will be used.
Answer: C
Explanation:
"Testing with diverseand representative datasets appropriate for how the model will be used aligns with Salesforce's Trusted AI Principle of Inclusivity. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences.Testing with diverse and representative datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain."
NEW QUESTION # 62
Which best describes the different between predictive AI and generative AI?
- A. Predictive new and original output for a given input.
- B. 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. - C. 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
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 # 63
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. Multi-Select Picklist
- B. Rich Text Area
- C. Text
Answer: C
Explanation:
"A text fieldtype 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 # 64
What is a possible outcome of poor data quality?
- A. AI predictions become more focused and less robust.
- B. AI models maintain accuracy but have slower response times.
- C. Biases in data can be inadvertently learned and amplified by AI systems.
Answer: C
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 # 65
What is machine learning?
- A. AI that creates new content
- B. A data model used in Salesforce
- C. AI that can grow its intelligence
Answer: B
Explanation:
Explanation
"A data model is a machine learning feature used in Salesforce. A data model is a representation or abstraction of a real-world phenomenon or process using data structures and algorithms. A data model can be used to describe, analyze, or predict various aspects of the phenomenon or process using machine learning techniques."
NEW QUESTION # 66
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. Multi-Select Picklist
- B. Rich Text Area
- 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 # 67
What is the rile of data quality in achieving AI business Objectives?
- A. Data quality is important for maintain Ai data storage limits
- B. Data quality is required to create accurate AI data insights.
- C. Data quality is unnecessary because AI can work with all data types.
Answer: B
Explanation:
"Data quality is required to create accurate AI data insights. 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. Data quality can also affect the accuracy and validity of AI data insights, as they reflect the quality of the data used or generated by AI systems."
NEW QUESTION # 68
What is an implication of user consent in regard to AI data privacy?
- A. AI infringes on privacy when user consent is not obtained.
- B. AI ensures complete data privacy by automatically obtaining user consent.
- C. AI operates Independently of user privacy and consent.
Answer: A
Explanation:
"AI infringes on privacy when user consent is not obtained. User consent is the permission or agreement given by a user to allow their personal data to be collected, used, shared, or stored byothers. User consent is an important aspect of data privacy, which is the right of individuals to control how their personal data is handled by others. AI infringes on privacy when user consent is not obtained because it violates the user's rights and preferences regarding their personal data."
NEW QUESTION # 69
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. Autofill
- B. Validation rule
- C. Duplicate matching rule
Answer: B
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 # 70
What is a key characteristic of machine learning in the context of AI capabilities?
- A. Relies on preprogrammed rules to make decisions
- B. Can perfectly mimic human intelligence anddecision-making
- C. Uses algorithms to learn from data and make decisions
Answer: C
Explanation:
"Machine learning is a key characteristic of AI capabilities that uses algorithms to learn from data and make decisions. Machine learning is a branch of AI that enables computers to learn from data without being explicitly programmed. Machine learning algorithms can analyze data, identify patterns, and make predictions or recommendations based on the data."
NEW QUESTION # 71
Cloud kicks wants to decrease the workload for its customer care agents by implementing a chatbot on its website that partially deflects incoming cases by answering frequency asked questions Which field of AI is most suitable for this scenario?
- A. Predictive analytics
- B. Computer vision
- C. Natural language processing
Answer: C
Explanation:
Explanation
"Natural language processing is the field of AI that is most suitable for this scenario. Natural language processing (NLP) is a branch of AI that enables computers to understand and generate natural language, such as speech or text. NLP can be used to create conversational interfaces that can interact with users using natural language, such as chatbots. Chatbots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the user's intent and context."
NEW QUESTION # 72
What is the best method to safeguard customer data privacy?
- A. Automatically anonymize all customer data.
- B. Track customer data consent preferences.
- C. Archive customer data on a recurring schedule.
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 # 73
A service leader wants use AI tohelp customer resolve their issues quicker in a guided self-serve application.
Which Einstein functionality provides the best solution?
- A. Bots
- B. Case Classification
- C. Recommendation
Answer: A
Explanation:
"Bots provide the best solution for a service leader whowants to use AI to help customers resolve their issues quicker in a guided self-serve application. Bots are a feature that uses natural language processing (NLP) and natural language understanding (NLU) to create conversational interfaces that can interactwith customers using text or voice. Bots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the customer's intent and context."
NEW QUESTION # 74
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. Survivorship
- B. Societal
- C. Confirmation
Answer: C
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 # 75
Which features of Einstein enhance sales efficiency and effectiveness?
- A. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
- B. Opportunity Scoring, Lead Scoring, Account Insights
- C. Opportunity List View, Lead List View, Account List view
Answer: B
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 # 76
What is a key challenge of human AI collaboration in decision-making?
- A. Reduce the need for human involvement in decision-making processes
- B. Leads to move informed and balanced decision-making
- C. Creates a reliance on AI, potentially leading to less critical thinking and oversight
Answer: C
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 # 77
What role does data quality play in the ethical us of AI applications?
- A. High-quality data ensures the process of demographic attributes requires for personalized campaigns.
- B. High-quality data is essential for ensuringunbased and for fair AI decisions, promoting ethical use, and preventing discrimi...
- C. Low-quality data reduces the risk of unintended bias as the datais not overfitted to demographic groups.
Answer: B
Explanation:
"High-quality data is essential for ensuring unbiased and fair AI decisions, promoting ethical use, and preventing discrimination. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can help ensure unbiased and fair AI decisions by providing a balanced and representative sample of the target population or domain. High-quality data can also help promote ethical use and prevent discrimination by respecting the rights and preferences of users regarding their personal data."
NEW QUESTION # 78
Cloud kicks wants to decrease the workload for its customer care agents by implementing a chatbot on its website that partially deflects incoming cases by answering frequency asked questions Which field of AI is most suitable for this scenario?
- A. Predictive analytics
- B. Computer vision
- C. Natural language processing
Answer: C
Explanation:
"Natural language processing is the field of AI that is most suitable for this scenario. Natural language processing (NLP) is a branch of AI that enables computers to understand and generate natural language, such as speech or text. NLP can be used to create conversational interfaces that can interact with users using natural language, such as chatbots. Chatbots can help automate and streamline customer service processes by providing answers, suggestions, or actions based on the user's intent and context."
NEW QUESTION # 79
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic...
- A. Cryptographic
- B. Geographic
- C. Geographic
Answer: C
Explanation:
"Demographic data is thedata that Salesforce automatically excludes from Marketing Cloud Einstein engagement model training to mitigate bias and ethical concerns. 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. Salesforce excludes demographic data from Marketing Cloud Einstein engagement model training to mitigate bias and ethical concerns by ensuring that the models are based on behavioral data rather than personal data."
NEW QUESTION # 80
What is the most likely impact that high-quality data will have on customer relationships?
- A. Improved customer trust and satisfaction
- B. Higher customer acquisition costs
- C. Increased brand loyalty
Answer: A
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 # 81
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