[2025年01月08日] 完全版には更新されたのはAI Associate（Salesforce-AI-Associate）認定サンプル問題
最新のSalesforce Salesforce-AI-Associateリアル試験問題集PDF
Salesforce Salesforce-AI-Associate 認定試験の出題範囲：
| トピック | 出題範囲 |
|---|---|
| トピック 1 |
|
| トピック 2 |
|
| トピック 3 |
|
| トピック 4 |
|
質問 # 17
What is the role of Salesforce Trust AI principles in the context of CRM system?
- A. Outlining the technical specifications for AI integration
- B. Guiding ethical and responsible use of AI
- C. Providing a framework for AI data model accuracy
正解：B
解説：
"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 practicesfor 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."
質問 # 18
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. Computer vision
- B. Predictive analytics
- C. Natural language processing
正解：C
解説：
"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."
質問 # 19
Cloud Kicks wants to use AI to enhance its sales processesand 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
正解：C
解説：
"Einstein Lead Scoring and Case Classification are thecapabilities that Cloud Kicks should use to enhance its sales processes and customer support. Einstein Lead Scoring and Case Classification are features that use AI tooptimize sales and service processes by providing insights and recommendations based ondata. 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."
質問 # 20
A healthcare company implements an algorithm to analyze patient data and assist in medical diagnosis.
Which primary role does data Quality play In this AI application?
- A. Reduced need for healthcare expertise in interpreting AI outouts
- B. Enhanced accuracy and reliability of medical predictions and diagnoses
- C. Ensured compatibility of AI algorithms with the system's Infrastructure
正解：B
解説：
Explanation
"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."
質問 # 21
What is the significance of explainability of trusted AI systems?
- A. Increases the complexity of AI models
- B. Describes how Al models make decisions
- C. Enhances the security and accuracy of AI models
正解：B
解説：
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.
質問 # 22
How does a data quality assessment impact business outcome for companies using AI?
- A. Accelerates the delivery of new AI solutions
- B. Improves the speed of AI recommendations
- C. Provides a benchmark for AI predictions
正解：C
解説：
Explanation
"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."
質問 # 23
Cloud Kicks wants to develop a solution to predict customers product interests based on historical data. 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. Consistency
- B. Accuracy
- C. Completeness
正解：A
解説：
Explanation
"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."
質問 # 24
What is a key challenge of human AI collaboration in decision-making?
- A. Creates a reliance on AI, potentially leading to less critical thinking and oversight
- B. Leads to move informed and balanced decision-making
- C. Reduce the need for human involvement in decision-making processes
正解：A
解説：
"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."
質問 # 25
What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?
- A. Ensuring transparency In Al-driven recommendations and predictions
- B. Taking responsibility for one's actions toward customers, partners, and society
- C. Safeguarding fundamental human rights and protecting sensitive data
正解：B
解説：
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."
質問 # 26
What is an example of ethical debt?
- A. Launching an AI feature after discovering a harmful bias
- B. Violating a data privacy law and falling to pay fines
- C. Delaying an AI product launch to retrain an AI data model
正解：A
解説：
"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 AIsystems. 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."
質問 # 27
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
正解：C
解説：
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."
質問 # 28
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
正解：A
解説：
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."
質問 # 29
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
正解：A
解説：
"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."
質問 # 30
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. Duplication
- B. Consistency
- C. Age
正解：B
解説：
Explanation
"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."
質問 # 31
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.
Whichdata quality dimension Is essential for this custom application?
- A. Duplication
- B. Consistency
- C. Age
正解：B
解説：
"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."
質問 # 32
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 programminglanguage
- C. To understand and generate human language
正解：C
解説：
"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."
質問 # 33
What is the significance of explainability of trusted AI systems?
- A. Increases the complexity of AI models
- B. Describes how Al models make decisions
- C. Enhances the security and accuracy of AI models
正解：B
解説：
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.
質問 # 34
What is the role of Salesforce Trust AI principles in the context of CRM system?
- A. Outlining the technical specifications for AI integration
- B. Guiding ethical and responsible use of AI
- C. Providing a framework for AI data model accuracy
正解：B
解説：
Explanation
"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."
質問 # 35
A sales manager wants to use AI to help sales representatives log their calls quicker and more accurately.
Which functionality provides the best solution?
- A. Auto-Generated Sales Tasks
- B. Call Summaries
- C. Sales Dialer
正解：B
解説：
The best functionality to help sales representatives log their calls quicker and more accurately is the use of AI-generated Call Summaries. This feature leverages AI to analyze voice data from sales calls and automatically generate concise summaries and actionable insights, which are then logged into the CRM system. This not only speeds up the process of recording call details but also enhances the accuracy of the data captured, reducing the likelihood of human error and ensuring that important details are not missed.
Salesforce provides AI tools that integrate with telephony solutions to enable these capabilities, enhancing the efficiency of sales operations. For more information on Salesforce AI features like Einstein Call Coaching that support this functionality, visit Salesforce Einstein Call Coaching.
質問 # 36
What is a Key consideration regarding data quality in AI implementation?
- A. Data's role in training and fine-tuning Salesforce AI models
- B. Techniques from customizing AI features in Salesforce
- C. Integration process of AI models with Salesforce workflows
正解：A
解説：
Explanation
"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."
質問 # 37
......
Salesforce Salesforce-AI-Associate問題集で一発合格を目指すならこれ！：https://www.goshiken.com/Salesforce/Salesforce-AI-Associate-mondaishu.html
Salesforce-AI-Associate練習テスト問題更新されたのは103問があります：https://drive.google.com/open?id=1JaIObAFJ0wPoCfJSjgn1QlW5YuTgXwHg