Get ready to pass your Salesforce Associate AI Certification exam with ease! In this video, we cover the most important questions and answers you need to know to succeed. Whether you’re a beginner or just brushing up on your knowledge, this guide provides clear explanations and expert tips to help you understand core Salesforce concepts. We’ll dive into topics like Salesforce basics, data management, automation, and more. Don’t miss out on this valuable resource to help you ace your exam and kickstart your Salesforce journey!
Question: 1
What is a benefit of a diverse, balanced, and large dataset?
A. Training time
B. Data privacy
C. Model accuracy
Answer: C
“Model accuracy is a benefit of a diverse, balanced, and large dataset. A diverse dataset can capture a variety of features and patterns that are relevant for the AI task. A balanced dataset can avoid overfitting or underfitting the model to a specific subset of data. A large dataset can provide enough information for the model to learn from and generalize well to new data.”
Question: 2
What are the three commonly used examples of AI in CRM?
A. Predictive scoring, reporting, Image classification
B. Predictive scoring, forecasting, recommendations
C. Einstein Bots, face recognition, recommendations
Answer: B
“Predictive scoring, forecasting, and recommendations are three commonly used examples
of AI in CRM. Predictive scoring can help prioritize leads, opportunities, and customers based on their likelihood to convert, churn, or buy. Forecasting can help predict future sales, revenue, or demand based on historical data and trends. Recommendations can help suggest the best products, services, or actions for each customer based on their preferences, behavior, and needs.”
Question: 3
Cloud Kicks wants to optimize its business operations by incorporating AI into its CRM. What should the company do first to prepare its data for use with AI?
A. Remove biased data.
B. Determine data availability.
C. Determine data outcomes.
Answer: B
Before using AI to optimize business operations, the company should first assess the availability and quality of its data. Data is the fuel for AI, and without sufficient and relevant data, AI cannot produce accurate and reliable results. Therefore, the company should identify what data it has, where it is stored, how it is accessed, and how it is maintained. This will help the company understand the feasibility and scope of its AI projects.
Question: 4
A healthcare company implements an algorithm to analyze patient data and assist in medical di ag nosis.
Which primary role does data Quality play In this AI application?
A. Enhanced accuracy and reliability of medical predictions and diagnoses
B. Ensured compatibility of AI algorithms with the system's Infrastructure
C. Reduced need for healthcare expertise in interpreting AI outouts
Answer: A
“Data quality plays a crucial role in enhancing the accuracy and reliability of medical predictions and diagnoses. Poor data quality can lead to inaccurate or misleading results, which can have serious consequences for patients’ health and well-being. Therefore, it is important to ensure that the data used for AI applications in healthcare is accurate, complete, consistent, and relevant.”
Question: 5
What are some of the ethical challenges associated with AI development?
A. Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes
B. Implicit transparency of AI systems, which makes It easy for users to understand and trust their decisions
C. Inherent neutrality of AI systems, which eliminates any potential for human bias in decision-
making.
Answer: A
“Some of the ethical challenges associated with AI development are the potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes. Human bias can arise from the data used to train the models, the design choices made by the developers, or the interpretation of the results by the users. Lack of transparency can make it difficult to understand how and why AI systems make certain decisions, which can affect trust, accountability, and fairness.”
Question: 6
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. Accuracy
C. Consistency
Answer: C
“Consistency is the data quality dimension that 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.”
Question: 7
How is natural language processing (NLP) used in the context of AI capabilities?
A. To cleanse and prepare data for AI implementations
B. To interpret and understand programming language
C. To understand and generate human language
Answer: C
“Natural language processing (NLP) is used in the context of AI capabilities to understand and generate human language. NLP can enable AI systems to interact with humans using natural language, such as speech or text. NLP can also enable AI systems to analyze and extract information from natural language data, such as documents, emails, or social media posts.”
Question: 8
What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?
A. Testing models with diverse datasets
B. Striving for model explain ability
C. Working with human rights experts
Answer: A
“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 models with diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain.”
Question: 9
Cloud Kicks wants to create a custom service analytics application to analyze cases in Salesforce. The application should rely on accurate data to ensure efficient case resolution.
Which data quality dimension Is essential for this custom application?
A. Consistency
B. Duplication
C. Age
Answer: A
“Consistency is the data quality dimension that is essential for creating a custom service analytics application to analyze cases in Salesforce. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources. Consistent data can ensure that the custom application can accurately and efficiently analyze cases and provide meaningful insights.”
Question: 10
What should organizations do to ensure data quality for their AI initiatives?
A. Collect and curate high-quality data from reliable sources.
B. Rely on AI algorithms to automatically handle data quality issues.
C. Prioritize model fine-tuning over data quality improvements.
Answer: A
“Organizations should collect and curate high-quality data from reliable sources to ensure data quality for their AI initiatives. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. Reliable sources mean that the data is trustworthy, credible, and authoritative. Collecting and curating high-quality data from reliable sources can improve the performance and reliability of AI systems.”
Question: 11
Which Einstein capability uses emails to create content for Knowledge articles?
A. Generate
B. Discover
C. Predict
Answer: A
“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.”
Question: 12
Which type of bias results from data being labeled according to stereotypes?
A. Association
B. Societal
C. Interaction
Answer: B
“Societal bias results from data being labeled according to stereotypes. Societal bias is a type of bias that reflects the assumptions, norms, or values of a specific society or culture. For example, societal bias can occur when data is labeled based on gender, race, ethnicity, or religion stereotypes.”
Question: 13
Salesforce defines bias as using a person's Immutable traits to classify them or market to them. Which potentially sensitive attribute is an example of an immutable trait?
A. Financial status
B. Nickname
C. Email address
Answer: A
“Financial status is an example of an immutable trait. Immutable traits are characteristics that are inherent, fixed, or unchangeable. For example, financial status is an immutable trait because it is determined by factors beyond one’s control, such as birth, inheritance, or economic conditions.
Nickname and email address are not immutable traits because they can be changed by choice or preference.”
Question: 14
Cloud Kicks relies on data analysis to optimize its product recommendation; however, CK encounters a recurring Issue of Incomplete customer records, with missing contact Information and incomplete purchase histories.
How will this incomplete data quality impact the company's operations?
A. The accuracy of product recommendations is hindered.
B. The diversity of product recommendations Is Improved.
C. Theresponsetimeforproductrecommendationsisstalled.
Answer: A
“The incomplete data quality will impact the company’s operations by hindering the accuracy of product recommendations. Incomplete data means that the data is missing some values or attributes that are relevant for the AI task. Incomplete data can affect the performance and reliability of AI models, as they may not have enough information to learn from or make accurate predictions. For example, incomplete customer records can affect the quality of product recommendations, as the AI model may not be able to capture the customers’ preferences, behavior, or needs.”
Question: 15
What are some key benefits of AI in improving customer experiences in CRM?
A. ImprovesCRMsecurityprotocols,safeguardingsensitivecustomerdatafrompotentialbreaches and threats
B. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions
C. Fully automates the customer service experience, ensuring seamless automated interactions with customers
Answer: B
“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.”
Question: 16
How does an organization benefit from using AI to personalize the shopping experience of online customers?
A. Customers are more likely to share personal information with a site that personalizes their experience.
B. Customers are more likely to be satisfied with their shopping experience.
C. Customers are more likely to visit competitor sites that personalize their experience.
Answer: B
“An organization benefits from using AI to personalize the shopping experience of online customers by increasing customer satisfaction. AI can help provide customized and relevant product recommendations, offers, or content based on the customers’ preferences, behavior, or needs. AI can also help create a more engaging and interactive shopping experience by using natural language processing (NLP) or computer vision techniques. Personalized shopping experiences can improve customer satisfaction by meeting their expectations, needs, and interests.”
Question: 17
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
“Testing with diverse and 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.”
Question: 18
Cloud Kicks wants to develop a solution to predict customers product interests based on historical data
a. The company found that employees from one region use a text field to capture the product category, while employees from all other locations use a plckllst.
Which data quality dimension is affected in this scenario?
A. Completeness
B. Accuracy
C. Consistency
Answer: C
“Consistency is the data quality dimension that is affected in this scenario. 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. For example, using different field types for the same attribute can affect the consistency of the data.”
Question: 19
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. Implement Salesforce's Trusted AI Principles.
C. Use demographic data to identify minority groups.
Answer: B
“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.”
Question: 20
Which features of Einstein enhance sales efficiency and effectiveness?
A. Opportunity List View, Lead List View, Account List view
B. Opportunity Scoring, Opportunity List View, Opportunity Dashboard
C. Opportunity Scoring, Lead Scoring, Account Insights
Answer: C
“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.”
Question: 21
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. Confirmation
B. Survivorship
C. Societal
Answer: A
“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.”
Question: 22
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
A. Safeguarding fundamental human rights and protecting sensitive data
B. Taking responsibility for one's actions toward customers, partners, and society
C. Ensuring transparency In Al-driven recommendations and predictions
Answer: B
“The main focus of the Accountability principle in Salesforce’s Trusted AI Principles is taking responsibility for one’s actions toward customers, partners, and society. Accountability means that AI systems should be designed and developed with respect for the impact and consequences of their actions on others. Accountability also means that AI developers and users should be aware of and adhere to the ethical, legal, and regulatory standards and expectations of their industry and domain.”
Question: 23
What is a sensitive variable that car esc to bias?
A. Education level
B. Country
C. Gender
Answer: C
“Gender is a sensitive variable that can lead to bias. A sensitive variable is a variable that can potentially cause discrimination or unfair treatment based on a person’s identity or characteristics.
For example, gender is a sensitive variable because it can affect how people are perceived, treated,
or represented by AI systems.”
Question: 24
A marketing manager wants to use AI to better engage their customers. Which functionality provides the best solution?
A. Journey Optimization
B. Bring Your Own Model
C. Einstein Engagement
Answer: C
“Einstein Engagement provides the best solution for a marketing manager who wants to use AI to better engage their customers. Einstein Engagement is a feature that uses AI to optimize email marketing campaigns by providing insights and recommendations on the best time, frequency, content, and subject lines to send emails to each customer. Einstein Engagement can help increase customer engagement, retention, and loyalty by delivering personalized and relevant messages.”
Question: 25
A Salesforce administrator creates a new field to capture an order's destination country. Which field type should they use to ensure data quality?
A. Text
B. Picklist
C. Number
Answer: B
“A picklist field type should be used to ensure data quality for capturing an order’s destination country. A picklist field type allows the user to select one or more predefined values from a list. A picklist field type can ensure data quality by enforcing consistency, accuracy, and completeness of the data values.”
Question: 26
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 how Prediction Builder works and a link to Salesforce's Trusted AI Principles
B. An explanation of the prediction's rationale and a model card that describes how the model was created.
C. A marketing article of the product that clearly outlines the or product's capabilities and features
Answer: B
“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.”
Question: 27
How does the "right of least privilege" reduce the risk of handling sensitive personal data?
A. By limiting how many people have access to data
B. By reducing how many attributes are collected
C. By applying data retention policies
Answer: A
“The “right of least privilege” reduces the risk of handling sensitive personal data by limiting how many people have access to data. The “right of least privilege” is a security principle that states that each user or system should have the minimum level of access or privilege necessary to perform their tasks or functions. The “right of least privilege” can help protect sensitive personal data from unauthorized access, misuse, or leakage.”
Question: 28
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
“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.”
Question: 29
What is the key difference between generative and predictive AI?
A. Generative AI creates new content based on existing data and predictive AI analyzes existing data.
B. Generative AI finds content similar to existing data and predictive AI analyzes existing data.
C. Generative AI analyzes existing data and predictive AI creates new content based on existing data.
Answer: A
“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.”
Question: 30
What is a key benefit of effective interaction between humans and AI systems?
A. Leads to more informed and balanced decision making
B. Alerts humans to the presence of biased data
C. Reduces the need for human involvement
Answer: A
“A key benefit of effective interaction between humans and AI systems is that it leads to more informed and balanced decision making. Effective interaction means that humans and AI systems can communicate and collaborate with each other in a clear, natural, and respectful way. Effective interaction can help leverage the strengths and complement the weaknesses of both humans and AI systems. Effective interaction can also help increase trust, confidence, and satisfaction in using AI systems.”
Question: 31
What is a key characteristic of machine learning in the context of AI capabilities?
A. Uses algorithms to learn from data and make decisions
B. Relies on preprogrammed rules to make decisions
C. Can perfectly mimic human intelligence and decision-making
Answer: A
“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.”
Question: 32
Cloud Kicks wants to ensure that multiple records for the same customer are removed in Salesforce. Which feature should be used to accomplish this?
A. Duplicate management
B. Trigger deletion of old records
C. Standardized field names
Answer: A
“Duplicate management should be used to remove multiple records for the same customer in Salesforce. Duplicate management is a feature that helps prevent and manage duplicate records in Salesforce. Duplicate management can help define matching rules, duplicate rules, and alert messages to detect and merge duplicate records.”
Question: 33
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. Text
C. Rich Text Area
Answer: B
“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.”
Question: 34
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
“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.”
Question: 35
To avoid introducing unintended bias to an AI model, which type of data should be omitted?
A. Transactional
B. Engagement
C. Demographic
Answer: C
“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.”
Question: 36
What is an implication of user consent in regard to AI data privacy?
A. AI ensures complete data privacy by automatically obtaining user consent.
B. AI infringes on privacy when user consent is not obtained.
C. AI operates Independently of user privacy and consent.
Answer: B
“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 by others. 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.”
Question: 37
How does data quality impact the trustworthiness of Al-driven decisions?
A. The use of both low-quality and high-quality data can improve the accuracy and reliability of AI- driven decisions.
B. High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.
C. Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.
Answer: B
“High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users. High-quality data means that the data is accurate, complete, consistent, relevant, and timely for the AI task. High-quality data can improve the performance and reliability of AI systems, as they have enough and correct information to learn from and make accurate predictions. High-quality data can also improve the trustworthiness of AI-driven decisions, as users can have more confidence and satisfaction in using AI systems.”
Question: 38
Cloud Kicks learns of complaints from customers who are receiving too many sales calls and emails. Which data quality dimension should be assessed to reduce these communication Inefficiencies?
A. Duplication
B. Usage
C. Consent
Answer: A
“Duplication is the data quality dimension that should be assessed to reduce communication inefficiencies. Duplication means that the data contains multiple copies or instances of the same record or value. Duplication can cause confusion, errors, or waste in data analysis and processing. For example, duplication can lead to communication inefficiencies if customers receive multiple calls or emails from different sources for the same purpose.”
Question: 39
A developer is tasked with selecting a suitable dataset for training an AI model in Salesforce to accurately predict current customer behavior.
What Is a crucial factor that the developer should consider during selection?
A. Number of variables ipn the dataset
B. Size of the dataset
C. Age of the dataset
Answer: B
“The size of the dataset is a crucial factor that the developer should consider during selection. The size of the dataset refers to the amount or volume of data available for training an AI model. The size of the dataset can affect the feasibility and quality of the AI model, as well as the choice of AI techniques and tools. The size of the dataset should be large enough to provide sufficient information for the AI model to learn from and generalize well to new data.”
Question: 40
What is machine learning?
A. AI that can grow its intelligence
B. AI that creates new content
C. A data model used in Salesforce
Answer: C
“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.”
Question: 41
A service leader wants use AI to help customer resolve their issues quicker in a guided self-serve application.
Which Einstein functionality provides the best solution?
A. Case Classification
B. Bots
C. Recommendation
Answer: B
“Bots provide the best solution for a service leader who wants 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 interact with 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.”
Question: 42
Why is it critical to consider privacy concerns when dealing with AI and CRM data?
A. Ensures compliance with laws and regulations
B. Confirms the data is accessible to all users
C. Increases the volume of data collected
Answer: A
“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.”
Question: 43
Which action should be taken to develop and implement trusted generated AI with Salesforce’s safety guideline in mind?
A. Develop right-sized models to reduce our carbon footprint.
B. Create guardrails that mitigates toxicity and protect PII
C. Be transparent when AI has created and automatically delivered content.
Answer: B
“Creating guardrails that mitigate toxicity and protect PII is an action that should be taken to develop and implement trusted generative AI with Salesforce’s safety guideline in mind. Salesforce’s safety guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the safety and well-being of humans and the environment. Creating guardrails means implementing measures or mechanisms that can prevent or limit the potential harm or risk caused by AI systems. For example, creating guardrails can help mitigate toxicity by filtering out inappropriate or offensive content generated by AI systems. Creating guardrails can also help protect PII by masking or anonymizing personal or sensitive information generated by AI systems.”
Question: 44
What is a potential source of bias in training data for AI models?
A. The data is collected in area time from sources systems.
B. The data is skewed toward is particular demographic or source.
C. The data is collected from a diverse range of sources and demographics.
Answer: B
“A potential source of bias in training data for AI models is that the data is skewed toward a particular demographic or source. Skewed data means that the data is not balanced or representative of the target population or domain. Skewed data can introduce or exacerbate bias in AI models, as they may overfit or underfit the model to a specific subset of data. For example, skewed data can lead to bias if the data is collected from a limited or biased demographic or source, such as a certain age group, gender, race, location, or platform.”
Question: 45
In the context of Salesforce’s Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?
A. Empower users to off all skill level to build AI application with clicks, not code.
B. Empower users to contribute to the growing body of knowledge of leading AI research.
C. Empower users to solve challenging technical problems using neural networks.
Answer: A
“The principle of Empowerment primarily aims to achieve empowering users of all skill levels to build AI applications with clicks, not code. Empowerment is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for the empowerment and education of humans. Empowering users means enabling users to access, use, and benefit from AI systems regardless of their technical expertise or background. For example, empowering users means providing tools and platforms that allow users to build AI applications with clicks, not code, such as Einstein Prediction Builder or Einstein Discovery.”
Question: 46
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 a Data Management Strategy.
B. Build reports to expire the data quality.
C. Leverage data quality apps from AppExchange
Answer: C
“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.”
Question: 47
What should be done to prevent bias from entering an AI system when training it?
A. Use alternative assumptions.
B. Import diverse training data.
C. Include Proxy variables.
Answer: B
“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 and patterns 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.”
Question: 48
What is a Key consideration regarding data quality in AI implementation?
A. Techniques from customizing AI features in Salesforce
B. Data’s role in training and fine-tuning Salesforce AI models
C. Integration process of AI models with Salesforce workflows
Answer: B
“Data’s role in training and fine-tuning Salesforce AI models is a key consideration regarding data quality in AI implementation. 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’s role in training and fine-tuning Salesforce AI models means understanding how data is used to build, train, test, and improve AI models in Salesforce, such as Einstein Prediction Builder or Einstein Discovery.”
Question: 49
Cloud Kicks wants to use AI to enhance its sales processes and customer support. Which capacity should they use?
A. Dashboard of Current Leads and Cases
B. Sales path and Automaton Case Escalations
C. Einstein Lead Scoring and Case Classification
Answer: C
“Einstein Lead Scoring and Case Classification are the capabilities that Cloud Kicks should use to enhance its sales processes and customer support. Einstein Lead Scoring and Case Classification are features that use AI to optimize sales and service processes by providing insights and recommendations based on data. Einstein Lead Scoring can help prioritize leads based on their likelihood to convert, while Einstein Case Classification can help categorize and route cases based on their attributes.”
Question: 50
Which statement exemplifies Salesforces honesty guideline when training AI models?
A. Minimize the AI models carbon footprint and environment impact during training.
B. Ensure appropriate consent and transparency when using AI-generated responses.
C. Control bias, toxicity, and harmful content with embedded guardrails and guidance.
Answer: B
“Ensuring appropriate consent and transparency when using AI-generated responses is a statement that exemplifies Salesforce’s honesty guideline when training AI models. Salesforce’s honesty guideline is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for honesty and integrity in how they work and what they produce. Ensuring appropriate consent and transparency means respecting and honoring the choices and preferences of users regarding how their data is used or generated by AI systems. Ensuring appropriate consent and transparency also means providing clear and accurate information and documentation about the AI systems and their outputs.”
Question: 51
What Is a benefit of data quality and transparency as it pertains to bias in generated AI?
A. Chances of bIas and mitigated
B. Chances of bias are aggravated
C. Chances of bias are remove
Answer: A
“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. Dataquality 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.”
Question: 52
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. Sales data cleansing and customer support data governance
B. Machine learning models and chatbot predictions
C. Lead scoring, opportunity forecasting, and case classification
Answer: C
“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.”
Question: 53
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. The wrong product
C. Too much data
Answer: A
“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.”
Question: 54
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. Duplicate matching rule
C. Validation rule
Answer: C
“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.”
Question: 55
Cloud kicks wants to develop a solution to predict customers’ interest based on historical data
.The company found that employee region uses a text field to capture the product category while employee from all other locations use a picklist.
Which dimension of data quality is affected in this scenario?
A. Accuracy
B. Consistency
C. Completeness
Answer: B
“Consistency is the dimension of data quality that is affected in this scenario. 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. For example, using different field types for the same attribute can affect the consistency of the data.”
Question: 56
Cloud Kicks wants to use an AI mode to predict the demand for shoes using historical data on sales and regional characteristics.
What is an essential data quality dimension to achieve this goal?
A. Reliability
B. Volume
C. Age
Answer: A
“Reliability is an essential data quality dimension to achieve the goal of predicting the demand for shoes using historical data on sales and regional characteristics. Reliability means that the data values are trustworthy, credible, and authoritative for the AI task. Reliable data can improve the accuracy and confidence of AI predictions, as they reflect the true state or condition of the target population or domain. For example, reliable data can help predict the demand for shoes by using verified and validated sales and regional data.”
Question: 57
A sales manager wants to improve their processes using AI in Salesforce? Which application of AI would be most beneficial?
A. Lead soring and opportunity forecasting
B. Sales dashboards and reporting
C. Data modeling and management
Answer: A
“Lead scoring and opportunity forecasting are applications of AI that would be most beneficial for a sales manager who wants to improve their processes using AI in Salesforce. Lead scoring can help prioritize leads based on their likelihood to convert, while opportunity forecasting can help predict future sales or revenue based on historical data and trends. These applications of AI can help optimize sales processes by providing insights and recommendations that can increase sales efficiency and effectiveness.”
Question: 58
How does AI which CRM help sales representatives better understand previous customer interactions?
A. Creates, localizes, and translates product descriptions
B. Triggers personalized service replies
C. Provides call summaries
Answer: C
“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.”
Question: 59
What is the most likely impact that high-quality data will have on customer relationships?
A. Increased brand loyalty
B. Higher customer acquisition costs
C. Improved customer trust and satisfaction
Answer: C
“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.”
Question: 60
What is the role of Salesforce Trust AI principles in the context of CRM system?
A. Guiding ethical and responsible use of AI
B. Providing a framework for AI data model accuracy
C. Outlining the technical specifications for AI integration
Answer: A
“The role of Salesforce Trust AI principles in the context of CRM systems is guiding ethical and responsible use of AI. Salesforce Trust 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. The principles aim to ensure that AI systems are aligned with the values and interests of customers, partners, and society.”
Question: 61
What role does data quality play in the ethical us of AI applications?
A. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimi…
B. High-quality data ensures the process of demographic attributes requires for personalized campaigns.
C. Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups.
Answer: A
“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.”
Question: 62
What can bias in AI algorithms in CRM lead to?
A. Personalization and target marketing changes
B. Advertising cost increases
C. Ethical challenges in CRM systems
Answer: C
“Bias in AI algorithms in CRM can lead to ethical challenges in CRM systems. Bias means that AI algorithms favor or discriminate certain groups or outcomes based on irrelevant or unfair criteria. Bias can affect the fairness and ethics of CRM systems, as they may affect how customers are perceived, treated, or represented by AI algorithms. For example, bias can lead to ethical challenges in CRM systems if AI algorithms make inaccurate or harmful predictions or recommendations based on customers’ identity or characteristics.”
Question: 63
What is an example of ethical debt?
A. Violating a data privacy law and falling to pay fines
B. Launching an AI feature after discovering a harmful bias
C. Delaying an AI product launch to retrain an AI data model
Answer: B
“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.”
Question: 64
A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets.
Which Salesforce Trusted AI Principles is being practiced>
A. Transparency
B. Inclusivity
C. Accountability
Answer: B
“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.”
Question: 65
A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce’s Trusted AI Principle of Transparency?
A. Communicate how risk factors such as credit score can impact customer eligibility.
B. Flag sensitive variables and their proxies to prevent discriminatory lending practices.
C. Incorporate customer feedback into the model’s continuous training.
Answer: B
“Flagging sensitive variables and their proxies to prevent discriminatory lending practices is how they should implement Salesforce’s Trusted AI Principle of Transparency. Transparency is one of the Trusted AI Principles that states 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. Flagging sensitive variables and their proxies means identifying and marking variables that can potentially cause discrimination or unfair treatment based on a person’s identity or characteristics, such as age, gender, race, income, or credit score. Flagging sensitive variables and their proxies can help implement Transparency by allowing users to understand and evaluate the data used or generated by AI systems.”
Question: 66
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. Natural language processing
B. Computer vision
C. Predictive analytics
Answer: A
“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.”
Question: 67
What are the key components of the data quality standard?
A. Naming, formatting, Monitoring
B. Accuracy, Completeness, Consistency
C. Reviewing, Updating, Archiving
Answer: B
“Accuracy, Completeness, Consistency are the key components of the data quality standard. Data quality standard is a set of criteria or measures that define and evaluate the quality of data for a specific purpose or task. Data quality standard can vary by industry, domain, or application, but some common components are accuracy, completeness, and consistency. Accuracy means that the data values are correct and valid for the data attribute. Completeness means that the data values are not missing any relevant information for the data attribute. Consistency means that the data values are uniform and follow a common standard or format across different records, fields, or sources.”
Question: 68
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
“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 to generate 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.”
Question: 69
Which type of bias imposes a system ‘s values on others?
A. Societal
B. Automation
C. Association
Answer: A
“Societal bias is the type of bias that imposes a system’s values on others. Societal bias is a type of bias that reflects the assumptions, norms, or values of a specific society or culture. Societal bias can affect the fairness and ethics of AI systems, as they may affect how different groups or domains are perceived, treated, or represented by AI systems. For example, societal bias can occur when AI systems impose a system’s values on others, such as using Western standards of beauty or success to judge or rank people from other cultures.”
Question: 70
What is the rile of data quality in achieving AI business Objectives?
A. Data quality is unnecessary because AI can work with all data types.
B. Data quality is required to create accurate AI data insights.
C. Data quality is important for maintain Ai data storage limits
Answer: B
“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.”
Question: 71
What is a potential outcome of using poor-quality data in AI application?
A. AI model training becomes slower and less efficient
B. AI models may produce biased or erroneous results.
C. AI models become more interpretable
Answer: B
“A potential outcome of using poor-quality data in AI applications is that AI models may produce biased or erroneous results. Poor-quality data means that the data is inaccurate, incomplete, inconsistent, irrelevant, or outdated for the AI task. Poor-quality data 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. Poor-quality data can also introduce or exacerbate biases or errors in AI models, such as human bias, societal bias, confirmation bias, or overfitting or underfitting.”
Question: 72
The Cloud technical team is assessing the effectiveness of their AI development processes?
Which established Salesforce Ethical Maturity Model should the team use to guide the development of trusted AI solution?
A. Ethical AI Prediction Maturity Model
B. Ethical AI Process Maturity Model
C. Ethical AI practice Maturity Model
Answer: B
“The Ethical AI Process Maturity Model is the established Salesforce Ethical Maturity Model that the Cloud technical team should use to guide the development of trusted AI solutions. The Ethical AI Process Maturity Model is a framework that helps assess and improve the ethical and responsible practices and processes involved in developing and deploying AI systems. The Ethical AI Process Maturity Model consists of five levels of maturity: Ad Hoc, Aware, Defined, Managed, and Optimized. The Ethical AI Process Maturity Model can help guide the development of trusted AI solutions by providing a roadmap and best practices for achieving higher levels of ethical maturity.”
Question: 73
Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic…
A. Geographic
B. Geographic
C. Cryptographic
Answer: B
“Demographic data is the data 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.”
Question: 74
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
“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.”
Question: 75
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
“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.”
Question: 76
A system admin recognizes the need to put a data management strategy in place. What is a key component of data management strategy?
A. Naming Convention
B. Data Backup
C. Color Coding
Answer: B
Data Backup is a key component of a data management strategy. A data backup is a process of creating and storing copies of data in a separate location or device to prevent data loss or damage in case of a disaster, accident, or malicious attack. A data backup can help ensure data availability, reliability, and security by allowing data to be restored or recovered in the event of a data breach, corruption, or deletion. A data management strategy should include a data backup plan that defines the frequency, scope, method, and location of data backups, as well as the roles and responsibilities of the data backup team.
