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What is the significance of explainability of trusted AI systems?
A. Increases the complexity of AI models B. Enhances the security and accuracy of AI models C. Describes how Al models make decisions
Answer: C
Explanation: The significance of the explainability of trusted AI systems is that it describes
how AI models make decisions. Explainability is crucial for building trust and accountability
in AI systems, ensuring that users and stakeholders understand the decision-making
processes and outcomes generated by AI. This is particularly important in scenarios where
AI decisions impact personal or financial status, such as in credit scoring or healthcare
diagnostics. Salesforce emphasizes the importance of explainable AI through its ethical AI
practices, aiming to make AI systems more transparent and understandable. More details
about Salesforce’s approach to ethical and explainable AI can be found in Salesforce AI ethics resources at Salesforce AI Ethics.
Question # 2
Cloud Kicks wants to evaluate its data quality to ensure accurate and up-to-date records.Which type of records negatively impact data quality?
A. Structured B. Complete C. Duplicate
Answer: C
Explanation: Duplicate records negatively impact data quality by creating inconsistencies
and confusion in database management, leading to potential errors in customer
relationship management (CRM) systems like Salesforce. Duplicates can skew analytics
results, lead to inefficiencies in customer service, and result in redundant marketing efforts.
Salesforce offers various tools to identify and merge duplicate records, thereby maintaining
high data integrity. More about managing duplicate records in Salesforce and ensuring data
quality can be found in Salesforce’s documentation on duplicate management at
Salesforce Duplicate Management.
Question # 3
Cloud Kicks' latest email campaign is struggling to attract new customers.How can AI increase the company's customer email engagement?
A. Create personalized emails B. Resend emails to inactive recipients C. Remove invalid email addresses
Answer: A
Explanation: AI can significantly increase customer email engagement by creating
personalized emails. Salesforce Einstein AI enhances email marketing campaigns by
analyzing customer data and past interactions to tailor the content, timing, and
recommendations within emails. This personalization leads to higher engagement rates as
emails resonate more closely with individual preferences and behaviors. Salesforce
Marketing Cloud provides tools to leverage AI for crafting personalized email campaigns,
ensuring that emails are relevant and appealing to recipients. For more insights into how AI
can be used to enhance email marketing, see the Salesforce Marketing Cloud page at
Salesforce Marketing Cloud Email Studio.
Question # 4
A business analyst (BA) is preparing a new use case for Al. They run a report to check fornull values in the attributes they plan to use.Which data quality component Is the BA verifying by checking for null values?
A. Duplication B. Usage C. Completeness
Answer: C
Explanation: By checking for null values, a business analyst (BA) is verifying the data
quality component of completeness. Completeness refers to the absence of missing values
or gaps in the data, which is essential for the accuracy and reliability of reports and
analytics used in AI models. Null values can indicate incomplete data, which may adversely
affect the performance of AI applications by leading to incorrect predictions or insights.
Salesforce emphasizes the importance of data completeness for effective data analysis
and provides tools for data quality assessment and improvement. Details on handling data
completeness in Salesforce can be explored at Salesforce Help Data Management.
Question # 5
Cloud Kicks plans to use automated chat as its primary support channel.Which Einstein feature should they use?
A. Discovery B. Bots C. Next Best Action
Answer: B
Explanation: For Cloud Kicks, using automated chat as the primary support channel, the
recommended Einstein feature is Bots. Einstein Bots are designed to automate customer
interactions on common issues through chat and messaging platforms. They can handle
routine requests, provide quick answers to frequently asked questions, and escalate more
complex issues to human agents. Using Einstein Bots helps improve customer service
efficiency and speed, leading to enhanced customer satisfaction. To learn more about
setting up and optimizing Einstein Bots for a business, you can visit the Salesforce
documentation on Einstein Bots at Salesforce Einstein Bots.
Question # 6
Which type of AI can enhance customer service agents' email responses by analyzing thewritten content of previous emails?
A. Natural language processing B. Machine learning C. Deep learning
Answer: A
Explanation: Natural language processing (NLP) is the type of AI that can enhance
customer service agents' email responses by analyzing the written content of previous
emails. NLP technologies interpret and generate human language, allowing AI systems to
understand, respond to, and even anticipate customer needs based on email interactions.
This capability helps in crafting more relevant, accurate, and personalized email responses,
improving customer service quality. Salesforce utilizes NLP in its Einstein AI platform to
augment various customer service functions. More about Salesforce Einstein’s NLP
capabilities can be found on the Salesforce Einstein page at Salesforce Einstein NLP.
Question # 7
A sales manager is looking to enhance the quality of lead data in their CRM system.Which process will most likely help the team accomplish this goal?
A. Redesign the lead conversion process, B. Review and update missing lead information. C. Prioritize active leads quarterly.
Answer: B
Explanation: To enhance the quality of lead data in their CRM system, the most effective
process is to review and update missing lead information. This process involves identifying
incomplete records and filling in missing details, which can significantly improve the
accuracy and usefulness of lead data. Accurate and complete lead information is crucial for
effective lead scoring, prioritization, and follow-up, enhancing overall sales performance.
Salesforce CRM offers data quality tools and features that assist in regularly reviewing and
maintaining the accuracy of lead data. Information on managing lead data quality in
Salesforce can be found at Salesforce Lead Management.
Question # 8
A developer has a large amount of data, but it is scattered across different systems and isnot standardized.Which key data quality element should they focus on to ensure the effectiveness of the AImodels?
A. Performance B. Consistency C. Volume
Answer: B
Explanation: When data is scattered and not standardized, the key data quality element a
developer should focus on is consistency. Consistency refers to the uniformity and
standardization of data across different systems, which is crucial for integrating and
analyzing data effectively, especially when developing AI models. Inconsistent data can lead to errors in analysis, poor AI model performance, and misleading insights. Salesforce
provides tools and practices for ensuring data consistency, such as data integration and
management solutions that help standardize and synchronize data across platforms. For
more information on Salesforce data management, refer to the Salesforce data
management tools at Salesforce Data Management.
Question # 9
What are predictive analytics, machine learning, natural language processing (NLP), andcomputer vision?
A. Different types of data models used in Salesforce B. Different types of automation tools used in Salesforce C. Different types of AI that can be applied in Salesforce
Answer: C
Explanation: Predictive analytics, machine learning, natural language processing (NLP),
and computer vision are all types of artificial intelligence technologies that can be applied in
Salesforce to enhance various aspects of business operations and customer interactions.
Predictive analytics uses historical data to make predictions about future events. Machine
learning involves algorithms that can learn from and make decisions based on data. NLP is
concerned with the interactions between computers and humans using natural language,
and computer vision interprets and processes visual information from the world to make
sense of it in the way humans do. Salesforce harnesses these AI technologies, particularly
through its Einstein platform, to provide powerful tools that help businesses automate
tasks, make better decisions, and offer more personalized services. For more on how
Salesforce utilizes these AI technologies, you can explore the Einstein AI services
documentation at Salesforce Einstein.
Question # 10
What does the term "data completeness" refer to in the context of data quality?
A. The degree to which all required data points are present in the dataset B. The process of aggregating multiple datasets from various databases C. The ability to access data from multiple sources in real time
Answer: A
Explanation: Data completeness is a measure of data quality that assesses whether all
required data points are present in a dataset. It checks for missing values or gaps in data
necessary for accurate analysis and decision-making. In the context of Salesforce,
ensuring data completeness is crucial for the effectiveness of CRM operations, reporting,
and AI-driven applications like Salesforce Einstein, which rely on complete data to function
optimally. Salesforce provides various tools and features, such as data validation rules and
batch data import processes, that help maintain data completeness across its platform.
Detailed guidance on managing data quality in Salesforce can be found in the Salesforce
Help documentation on data management at Salesforce Help Data Management.
Question # 11
What is one technique to mitigate bias and ensure fairness in AI applications?
A. Ongoing auditing and monitoring of data that is used in AI applications B. Excluding data features from the Al application to benefit a population C. Using data that contains more examples of minority groups than majority groups
Answer: A
Explanation: A technique to mitigate bias and ensure fairness in AI applications is ongoing
auditing and monitoring of the data used in AI applications. Regular audits help identify and
address any biases that may exist in the data, ensuring that AI models function fairly and
without prejudice. Monitoring involves continuously checking the performance of AI
systems to safeguard against discriminatory outcomes. Salesforce emphasizes the
importance of ethical AI practices, including transparency and fairness, which can be
further explored through Salesforce’s AI ethics guidelines at Salesforce AI Ethics.
Question # 12
What are the potential consequences of an organization suffering from poor data quality?
A. Low employee morale, stock devaluation, and inability to attract top talent B. Revenue loss, poor customer service, and reputational damage C. Technical debt, monolithic system architecture, and slow ETL throughput
Answer: B
Explanation: The potential consequences of an organization suffering from poor data
quality include revenue loss, poor customer service, and reputational damage. Poor data
quality can lead to inaccurate analytics and decision-making, impacting customer
interactions, marketing strategies, and financial forecasting. These issues ultimately affect
customer satisfaction and could lead to financial losses and a damaged brand reputation.
Salesforce highlights the importance of maintaining high data quality for effective CRM and
AI applications, offering various tools and best practices to enhance data integrity. For
guidance on managing and improving data quality in Salesforce, see the Salesforce documentation on data quality at Salesforce Data Quality.
Question # 13
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
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.”
Question # 14
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
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.”
Question # 15
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
Explanation
“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 # 16
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
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.”
Question # 17
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
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.”
Question # 18
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
Explanation
“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 # 19
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
Explanation
“Conducting a series of Consequence Scanning workshops to support testing diverse datasets is an action that practices Salesforce’s Trusted AI Principle of Inclusivity. Inclusivity is one of the Trusted AI Principles that states that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Conducting Consequence Scanning workshops means engaging with various stakeholders to identify and assess the potential impacts and implications of AI systems on different groups or domains. Conducting Consequence Scanning workshops can help practice Inclusivity by ensuring that diverse datasets are used to test and evaluate AI systems.”
Question # 20
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
Explanation
“The key difference between generative and predictive AI is that generative AI creates new content based on existing data and predictive AI analyzes existing data. Generative AI is a type of AI that can generate novel content such as images, text, music, or video based on existing data or inputs. Predictive AI is a type of AI that can analyze existing data or inputs and make predictions or recommendations based on patterns or trends.”
Question # 21
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
Explanation
“An example of Salesforce’s Trusted AI Principle of Inclusivity in practice is testing models with diverse datasets. Inclusivity means that AI systems should be designed and developed with respect for diversity and inclusion of different perspectives, backgrounds, and experiences. Testing modelswith diverse datasets can help ensure that the models are fair, unbiased, and representative of the target population or domain.”
Question # 22
What is a sensitive variable that car esc to bias?
A. Education level B. Country C. Gender
Answer: C
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.”
Question # 23
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
Explanation
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 damagein 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.
Question # 24
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
“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.”
Question # 25
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
Explanation
“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 # 26
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
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.”
- Einstein Analytics Fundamentals (20%)
- Data Model and Management (15%)
- AI Model Building and Management (30%)
- Implementation and Consulting Best Practices (20%)
- Ethics and Privacy (15%)
Prerequisites
None, but experience with Salesforce recommended
Target Audience
Salesforce professionals, data analysts, AI enthusiasts
Exam Registration
Via Salesforce Certification website or testing centers
Cost
Approximately USD 200 (varies by region)
Retake Policy
Allowed after 14 days of first attempt, fees apply
Certification Validity
2 years, with maintenance exams required annually
Preparation Materials
Salesforce Trailhead modules, study guides, practice exams
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The Salesforce AI Associate exam is designed for individuals who want to demonstrate their knowledge and skills in using artificial intelligence (AI) technologies within the Salesforce ecosystem. It is suitable for developers, administrators, and consultants who work with AI features in Salesforce. Salesforce-AI-Associate Exam Details
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The Salesforce AI Associate exam consists of multiple-choice questions and is typically 60 minutes in duration. Salesforce AI Associate Exam Format
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The exam covers a range of topics including AI fundamentals, Salesforce Einstein, predictive modeling, and more. You can find a detailed exam outline on the Salesforce certification website. Salesforce AI Associate Exam Guide
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Sure! To prepare for the exam, it's important to study the official Salesforce documentation, complete Trailhead modules, and consider taking practice exams to assess your knowledge. Preparing for Salesforce Exams
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Salesforce provides official study materials, including Trailhead modules, certification guides, and practice exams, which are highly recommended for preparation. Salesforce Trailhead
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The cost of the Salesforce AI Associate exam may vary. Check the Salesforce certification website for the most up-to-date pricing information. Salesforce Certification Pricing
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