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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?. Autofill. Duplicate matching rule. Validation rule.

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.

What are the key components of the data quality standard?. Naming, formatting, Monitoring. Accuracy, Completeness, Consistency. Reviewing, Updating, Archiving.

What is an implication of user consent in regard to AI data privacy?. AI ensures complete data privacy by automatically obtaining user consent. AI infringes on privacy when user consent is not obtained. AI operates Independently of user privacy and consent.

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.

Which action should be taken to develop and implement trusted generated AI with Salesforce’s safety guideline in mind?. Develop right-sized models to reduce our carbon footprint. Create guardrails that mitigates toxicity and protect PII. Be transparent when AI has created and automatically delivered content.

What should organizations do to ensure data quality for their AI initiatives?. Collect and curate high-quality data from reliable sources. Rely on AI algorithms to automatically handle data quality issues. Prioritize model fine-tuning over data quality improvements.

How does AI which CRM help sales representatives better understand previous customer interactions?. Creates, localizes, and translates product descriptions. Triggers personalized service replies. Provides call summaries.

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.

Which best describes the different between predictive AI and generative AI?. Predictive new and original output for a given input. 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. 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.

Which type of bias results from data being labeled according to stereotypes?. Association. Societal. Interaction.

Which features of Einstein enhance sales efficiency and effectiveness?. Opportunity List View, Lead List View, Account List view. Opportunity Scoring, Opportunity List View, Opportunity Dashboard. Opportunity Scoring, Lead Scoring, Account Insights.

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.

To avoid introducing unintended bias to an AI model, which type of data should be omitted?. Transactional. Engagement. Demographic.

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.

Cloud Kicks wants to ensure that multiple records for the same customer are removed in Salesforce. Which feature should be used to accomplish this?. Duplicate management. Trigger deletion of old records. Standardized field names.

Which Einstein capability uses emails to create content for Knowledge articles?. Generate. Discover. Predict.

Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results? What to a potential mason for this?. Poor data quality. The wrong product. Too much data.

Which data does Salesforce automatically exclude from marketing Cloud Einstein engagement model training to mitigate bias and ethic…. Geographic. Demographic. Cryptographic.

What is a potential outcome of using poor-quality data in AI application?. AI model training becomes slower and less efficient. AI models may produce biased or erroneous results. AI models become more interpretable.

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.

What is a potential outcome of using poor-quality data in AI application?. AI model training becomes slower and less efficient. AI models may produce biased or erroneous results. AI models may produce biased or erroneous results.

What is the rile of data quality in achieving AI business Objectives?. Data quality is unnecessary because AI can work with all data types. Data quality is required to create accurate AI data insights. Data quality is important for maintain Ai data storage limits.

Which type of bias imposes a system 's values on others?. Societal. Automation. Association.

Which best describes the different between predictive AI and generative AI?. Predictive new and original output for a given input. 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. 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.

What are the key components of the data quality standard?. Naming, formatting, Monitoring. Accuracy, Completeness, Consistency. Reviewing, Updating, Archiving.

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?. Number of variables ipn the dataset. Size of the dataset. Age of the dataset.

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.

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?. Completeness. Accuracy. Consistency.

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.

What role does data quality play in the ethical us of AI applications?. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimination. High-quality data ensures the process of demographic attributes requires for personalized campaigns. Low-quality data reduces the risk of unintended bias as the data is not overfitted to demographic groups.

Why is it critical to consider privacy concerns when dealing with AI and CRM data?. Ensures compliance with laws and regulations. Confirms the data is accessible to all users. Increases the volume of data collected.

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.

What is a sensitive variable that car esc to bias?. Education level. Country. Gender.

Which Einstein capability uses emails to create content for Knowledge articles?. Generate. Discover. Predict.

Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results? What to a potential mason for this?. Poor data quality. The wrong product. Too much data.

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?. Case Classification. Bots. Recommendation.

What is a possible outcome of poor data quality?. AI models maintain accuracy but have slower response times. Biases in data can be inadvertently learned and amplified by AI systems. AI predictions become more focused and less robust.

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.

Which action should be taken to develop and implement trusted generated AI with Salesforce’s safety guideline in mind?. Develop right-sized models to reduce our carbon footprint. Create guardrails that mitigates toxicity and protect PII. Be transparent when AI has created and automatically delivered content.

Which type of bias imposes a system ‘s values on others?. Societal. Automation. Association.

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?. Autofill. Duplicate matching rule. Validation rule.

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.

What should organizations do to ensure data quality for their AI initiatives?. Collect and curate high-quality data from reliable sources. Rely on AI algorithms to automatically handle data quality issues. Prioritize model fine-tuning over data quality improvements.

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?. Reliability. Volume. Age.

What Is a benefit of data quality and transparency as it pertains to bias in generated AI?. Chances of bias are mitigated. Chances of bias are aggravated. Chances of bias are remove.

What should be done to prevent bias from entering an AI system when training it?. Use alternative assumptions. Import diverse training data. Include Proxy variables.

What are some key benefits of AI in improving customer experiences in CRM?. Improves CRM security protocols, safeguarding sensitive customer data from potential breaches and threats. Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions. Fully automates the customer service experience, ensuring seamless automated interactions with customers.

In Salesforce’s AI ethics, what does the principle ‘Responsible’ emphasize?. Maximizing profits using AI. Safeguarding human rights and data protection. Ensuring AI operates at maximum efficiency. Making AI systems visually appealing.

In the context of Salesforce AI, what does ‘Empowerment’ emphasize?. Making AI autonomous. Augmenting human capabilities with AI. Making AI systems faster. Making AI open-source.

What is the primary concern when dealing with ‘Algorithmic Bias’ in Salesforce AI?. Speed of algorithms. Cost of algorithms. Equitable treatment by AI systems. Open-source algorithms.

In the context of Salesforce AI, what does ‘Transparency’ emphasize?. Making AI systems visually appealing. Ensuring users understand the reasoning behind AI-driven recommendations. Making AI systems faster. Making AI open-source.

Which Salesforce feature emphasizes the importance of AI being paired with human ability?. Empowering. Transparent. Accountable. Inclusive.

Which of the following is a key consideration when implementing AI in Salesforce for improving sales forecasting?. The color scheme of the Salesforce dashboard. The number of users in the Salesforce system. The quality and consistency of historical sales data. The logo design of the company.

Which of the following is NOT a Salesforce AI product?. Einstein Analytics. Salesforce Cloud. Einstein Voice. Einstein Prediction Builder.

How does Salesforce AI primarily enhance the user experience in sales processes?. By automating routine tasks and reducing manual data entry. By providing real-time insights and predictive analytics to optimize sales strategies. By facilitating seamless collaboration between sales and marketing teams through shared insights. By offering advanced visualization tools for better data interpretation.

When integrating Salesforce AI into an existing system, which of the following challenges might a company face?. Ensuring data consistency between Salesforce AI and other platforms. Integrating AI predictions with legacy CRM systems. Handling the increased volume of data for AI processing. Managing the change in organizational workflows due to AI-driven insights.

What factors can determine the quality of data used for training AI models?. The age and consistency of the data. The volume and granularity of the data. The accuracy, completeness, and uniqueness of the data. The source and timeliness of the data.

What is a key milestone in the Ethical AI Practice Maturity Model?. Implementing AI without human intervention. Achieving transparency in AI decision-making processes. Ensuring AI models are trained on large datasets. Integrating AI into all business processes.

What is data cleansing in the context of generative AI in CRM?. Increasing the volume of data for better AI predictions. removing redundant CRM modules to streamline data flow. Correcting, removing, or handling corrupted, misformatted, or incomplete data. Upgrading to the latest CRM software version for better data compatibility.

What are Einstein Bots?. Advanced visualization tools within Salesforce. Automated data entry tools in Salesforce CRM. AI-driven chatbots in Salesforce for customer service automation. Predictive analytics tools for sales forecasting in Salesforce.

What is Einstein Knowledge?. A Salesforce tool for predictive analytics. An AI-driven chatbot system within Salesforce. A knowledge base system within Salesforce that uses AI to recommend articles and solutions. A visual analytics tool in Salesforce for creating interactive dashboards.

What is Einstein Prediction Builder?. A tool for creating custom AI models in Salesforce without code. A Salesforce feature for visualizing data patterns. An AI-driven system for customer support in Salesforce. A tool for integrating external AI models into Salesforce.

What is the benefit of using Salesforce AI for your business?. It only provides visual analytics for business data. It offers automated data entry solutions for CRM. It harnesses AI to provide insights, automate tasks, and personalize customer experiences. It exclusively focuses on chatbot solutions for customer support.

What is the difference between Einstein Discovery and Einstein Analytics?. Einstein Discovery is for data visualization while Einstein Analytics is for predictive modeling. Einstein Discovery offers insights and recommendations based on data, while Einstein Analytics provides a platform for creating interactive dashboards and reports. Einstein Discovery is a chatbot solution, while Einstein Analytics is a knowledge-base system. Einstein Discovery focuses on external data integration, while Einstein Analytics is for internal Salesforce data only.

What is the difference between Einstein Vision and Einstein Prediction?. Einstein Vision deals with image recognition, while Einstein Prediction focuses on forecasting business outcomes. Einstein Vision is a data visualization tool, while Einstein Prediction is for chatbot solutions. Einstein Vision is for creating AI models, while Einstein Prediction is for integrating external AI models. Einstein Vision focuses on text analysis, while Einstein Prediction is for image analysis.

How can you use Salesforce AI to build predictive models?. By manually inputting predictions based on intuition. Using Einstein Prediction Builder to create custom AI models without coding. By integrating third-party AI tools without using Salesforce’s native capabilities. By only using Salesforce reports and dashboards without AI features.

How can you use Salesforce AI to detect fraud and security threats?. By solely relying on manual transaction reviews. Using Einstein Anomaly Detection to automatically identify unusual patterns in data. By setting up basic email alerts for all transactions. By only monitoring user login activities.