Based on Official Syllabus Topics of Actual Salesforce Salesforce-AI-Associate Exam [Q33-Q51]

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Based on Official Syllabus Topics of Actual Salesforce Salesforce-AI-Associate Exam [Q33-Q51]

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Based on Official Syllabus Topics of Actual Salesforce Salesforce-AI-Associate Exam

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Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

Topic	Details
Topic 1	Describe the ethical challenges of AI Describe the elements components of data quality
Topic 2	Describe the importance of data quality Explain the basic principles and applications of AI within Salesforce
Topic 3	Identify CRM AI capabilities Differentiate between the types of AI and their capabilities
Topic 4	Apply Salesforce’s Trusted AI Principles to given scenarios Describe the benefits of AI as they apply to CRM
Topic 5	AI Capabilities in CRM Ethical Considerations of AI AI Fundamentals

NO.33 What is a sensitive variable that car esc to bias?

Education level

Country

Gender

Explanation
“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.”

NO.34 What can bias in AI algorithms in CRM lead to?

Personalization and target marketing changes

Advertising cost increases

Ethical challenges in CRM systems

Explanation
“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.”

NO.35 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?

Confirmation

Survivorship

Societal

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.”

NO.36 What is a key characteristic of machine learning in the context of AI capabilities?

Uses algorithms to learn from data and make decisions

Relies on preprogrammed rules to make decisions

Can perfectly mimic human intelligence and decision-making

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.”

NO.37 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?

Build a Data Management Strategy.

Build reports to expire the data quality.

Leverage data quality apps from AppExchange

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.”

NO.38 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?

Natural language processing

Computer vision

Predictive analytics

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.”

NO.39 To avoid introducing unintended bias to an AI model, which type of data should be omitted?

Transactional

Engagement

Demographic

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.”

NO.40 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?

Sales data cleansing and customer support data governance

Machine learning models and chatbot predictions

Lead scoring, opportunity forecasting, and case classification

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.”

NO.41 What is the main focus of the Accountability principle in Salesforce’s Trusted AI Principles?

Safeguarding fundamental human rights and protecting sensitive data

Taking responsibility for one’s actions toward customers, partners, and society

Ensuring transparency In Al-driven recommendations and predictions

Explanation
“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.”

NO.42 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?

Duplication

Usage

Consent

Explanation
“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.”

NO.43 Cloud Kicks wants to use AI to enhance its sales processes and customer support.
Which capacity should they use?

Dashboard of Current Leads and Cases

Sales path and Automaton Case Escalations

Einstein Lead Scoring and Case Classification

Explanation
“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.”

NO.44 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?

Financial status

Nickname

Email address

Explanation
“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.”

NO.45 A financial institution plans a campaign for preapproved credit cards?
How should they implement Salesforce’s Trusted AI Principle of Transparency?

Communicate how risk factors such as credit score can impact customer eligibility.

Flag sensitive variables and their proxies to prevent discriminatory lending practices.

Incorporate customer feedback into the model’s continuous training.

Explanation
“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.”

NO.46 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?

An explanation of how Prediction Builder works and a link to Salesforce’s Trusted AI Principles

An explanation of the prediction’s rationale and a model card that describes how the model was created

A marketing article of the product that clearly outlines the oroduct’s capabilities and features

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.”

NO.47 What is an example of ethical debt?

Violating a data privacy law and falling to pay fines

Launching an AI feature after discovering a harmful bias

Delaying an AI product launch to retrain an AI data model

Explanation
“Launching an AI feature after discovering a harmful bias is an example of ethical debt. Ethical debt is a term that describes the potential harm or risk caused by unethical or irresponsible decisions or actions related to AI systems. Ethical debt can accumulate over time and have negative consequences for users, customers, partners, or society. For example, launching an AI feature after discovering a harmful bias can create ethical debt by exposing users to unfair or inaccurate results that may affect their trust, satisfaction, or well-being.”

NO.48 What is a key challenge of human AI collaboration in decision-making?

Leads to move informed and balanced decision-making

Creates a reliance on AI, potentially leading to less critical thinking and oversight

Reduce the need for human involvement in decision-making processes

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.”

NO.49 In the context of Salesforce’s Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?

Empower users to off all skill level to build AI application with clicks, not code.

Empower users to contribute to the growing body of knowledge of leading AI research.

Empower users to solve challenging technical problems using neural networks.

Explanation
“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.”

NO.50 How does data quality impact the trustworthiness of Al-driven decisions?

The use of both low-quality and high-quality data can improve the accuracy and reliability of AI-driven decisions.

High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust among users.

Low-quality data reduces the risk of overfitting the model, improving the trustworthiness of the predictions.

Explanation
“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.”

NO.51 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?

Remove biased data.

Determine data availability.

Determine data outcomes.

Explanation
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.

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Based on Official Syllabus Topics of Actual Salesforce Salesforce-AI-Associate Exam [Q33-Q51]

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Based on Official Syllabus Topics of Actual Salesforce Salesforce-AI-Associate Exam [Q33-Q51]

Salesforce Salesforce-AI-Associate Exam Syllabus Topics:

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