Salesforce AI-Associate Exam Study Notes
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Questions and Answers

What is a benefit of a diverse, balanced, and large dataset?

  • Model accuracy (correct)
  • Data privacy
  • Training time

    • What are the three commonly used examples of AI in CRM?

  • Predictive scoring, reporting, Image classification
  • Predictive scoring, forecasting, recommendations (correct)
  • Einstein Bots, face recognition, recommendations

    • 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. (correct)
  • Determine data outcomes.

    • 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?

    <p>Enhanced accuracy and reliability of medical predictions and diagnoses</p> Signup and view all the answers

    What are some of the ethical challenges associated with AI development?

    <p>Potential for human bias in machine learning algorithms and the lack of transparency in AI decision-making processes</p> Signup and view all the answers

    Cloud Kicks discovered multiple variations of state and country values in contact records. Which data quality dimension is affected by this issue?

    <p>Consistency</p> Signup and view all the answers

    How is natural language processing (NLP) used in the context of AI capabilities?

    <p>To understand and generate human language</p> Signup and view all the answers

    What is an example of Salesforce's Trusted AI Principle of Inclusivity in practice?

    <p>Testing models with diverse datasets</p> Signup and view all the answers

    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?

    <p>Consistency</p> Signup and view all the answers

    What should organizations do to ensure data quality for their AI initiatives?

    <p>Collect and curate high-quality data from reliable sources.</p> Signup and view all the answers

    Which Einstein capability uses emails to create content for Knowledge articles?

    <p>Generate</p> Signup and view all the answers

    Which type of bias results from data being labeled according to stereotypes?

    <p>Societal</p> Signup and view all the answers

    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?

    <p>Financial status</p> Signup and view all the answers

    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?

    <p>The accuracy of product recommendations is hindered.</p> Signup and view all the answers

    What are some key benefits of AI in improving customer experiences in CRM?

    <p>Streamlines case management by categorizing and tracking customer support cases, identifying topics, and summarizing case resolutions</p> Signup and view all the answers

    How does an organization benefit from using AI to personalize the shopping experience of online customers?

    <p>Customers are more likely to be satisfied with their shopping experience.</p> Signup and view all the answers

    Cloud Kicks is testing a new AI model. Which approach aligns with Salesforce's Trusted AI Principle of Inclusivity?

    <p>Test with diverse and representative datasets appropriate for how the model will be used.</p> Signup and view all the answers

    Cloud Kicks wants to develop a solution to predict customers product interests based on historical dat 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 plcklist. Which data quality dimension is affected in this scenario?

    <p>Consistency</p> Signup and view all the answers

    Cloud Kicks wants to implement AI features on its Salesforce Platform but has concerns about potential ethical and privacy challenges. What should they consider doing to minimize potential AI bias?

    <p>Implement Salesforce's Trusted AI Principles.</p> Signup and view all the answers

    Which features of Einstein enhance sales efficiency and effectiveness?

    <p>Opportunity Scoring, Lead Scoring, Account Insights</p> Signup and view all the answers

    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?

    <p>Confirmation</p> Signup and view all the answers

    What is the main focus of the Accountability principle in Salesforce's Trusted AI Principles?

    <p>Taking responsibility for one's actions toward customers, partners, and society</p> Signup and view all the answers

    What is a sensitive variable that car esc to bias?

    <p>Gender</p> Signup and view all the answers

    A marketing manager wants to use AI to better engage their customers. Which functionality provides the best solution?

    <p>Einstein Engagement</p> Signup and view all the answers

    A Salesforce administrator creates a new field to capture an order's destination country. Which field type should they use to ensure data quality?

    <p>Picklist</p> Signup and view all the answers

    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?

    <p>An explanation of the prediction's rationale and a model card that describes how the model was created</p> Signup and view all the answers

    How does the "right of least privilege" reduce the risk of handling sensitive personal data?

    <p>By limiting how many people have access to data</p> Signup and view all the answers

    What is the best method to safeguard customer data privacy?

    <p>Track customer data consent preferences.</p> Signup and view all the answers

    What is the key difference between generative and predictive AI?

    <p>Generative AI creates new content based on existing data and predictive AI analyzes existing data.</p> Signup and view all the answers

    What is a key benefit of effective interaction between humans and AI systems?

    <p>Leads to more informed and balanced decision making</p> Signup and view all the answers

    What is a key characteristic of machine learning in the context of AI capabilities?

    <p>Uses algorithms to learn from data and make decisions</p> Signup and view all the answers

    Cloud Kicks wants to ensure that multiple records for the same customer are removed in Salesforce. Which feature should be used to accomplish this?

    <p>Duplicate management</p> Signup and view all the answers

    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?

    <p>Text</p> Signup and view all the answers

    What is a possible outcome of poor data quality?

    <p>Biases in data can be inadvertently learned and amplified by AI systems.</p> Signup and view all the answers

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

    <p>Demographic</p> Signup and view all the answers

    What is an implication of user consent in regard to AI data privacy?

    <p>AI infringes on privacy when user consent is not obtained.</p> Signup and view all the answers

    How does data quality impact the trustworthiness of AI-driven decisions?

    <p>High-quality data improves the reliability and credibility of AI-driven decisions, fostering trust among users.</p> Signup and view all the answers

    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?

    <p>Duplication</p> Signup and view all the answers

    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?

    <p>Size of the dataset</p> Signup and view all the answers

    What is machine learning?

    <p>A data model used in Salesforce</p> Signup and view all the answers

    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?

    <p>Bots</p> Signup and view all the answers

    Why is it critical to consider privacy concerns when dealing with AI and CRM data?

    <p>Ensures compliance with laws and regulations</p> Signup and view all the answers

    Which action should be taken to develop and implement trusted generated AI with Salesforce's safety guideline in mind?

    <p>Create guardrails that mitigates toxicity and protect PII</p> Signup and view all the answers

    What is a potential source of bias in training data for AI models?

    <p>The data is skewed toward is particular demographic or source.</p> Signup and view all the answers

    In the context of Salesforce's Trusted AI Principles what does the principle of Empowerment primarily aim to achieve?

    <p>Empower users to off all skill level to build AI application with clicks, not code.</p> Signup and view all the answers

    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?

    <p>Leverage data quality apps from AppExchange</p> Signup and view all the answers

    What should be done to prevent bias from entering an AI system when training it?

    <p>Import diverse training data.</p> Signup and view all the answers

    What is a Key consideration regarding data quality in AI implementation?

    <p>Data's role in training and fine-tuning Salesforce AI models</p> Signup and view all the answers

    Cloud Kicks wants to use AI to enhance its sales processes and customer support. Which capacity should they use?

    <p>C. Einstein Lead Scoring and Case Classification</p> Signup and view all the answers

    Which statement exemplifies Salesforces honesty guideline when training AI models?

    <p>B. Ensure appropriate consent and transparency when using AI-generated responses.</p> Signup and view all the answers

    What Is a benefit of data quality and transparency as it pertains to bias in generated AI?

    <p>A. Chances of bIas and mitigated</p> Signup and view all the answers

    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?

    <p>C. Lead scoring, opportunity forecasting, and case classification</p> Signup and view all the answers

    Cloud Kicks uses Einstein to generate predictions out is not seeing accurate results? What to a potential mason for this?

    <p>A. Poor data quality</p> Signup and view all the answers

    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?

    <p>C. Validation rule</p> Signup and view all the answers

    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?

    <p>B. Consistency</p> Signup and view all the answers

    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?

    <p>A. Reliability</p> Signup and view all the answers

    A sales manager wants to improve their processes using AI in Salesforce? Which application of AI would be most beneficial?

    <p>A. Lead soring and opportunity forecasting</p> Signup and view all the answers

    How does AI which CRM help sales representatives better understand previous customer interactions?

    <p>C. Provides call summaries</p> Signup and view all the answers

    What is the most likely impact that high-quality data will have on customer relationships?

    <p>C. Improved customer trust and satisfaction</p> Signup and view all the answers

    What is the role of Salesforce Trust AI principles in the context of CRM system?

    <p>A. Guiding ethical and responsible use of AI</p> Signup and view all the answers

    What role does data quality play in the ethical us of AI applications?

    <p>A. High-quality data is essential for ensuring unbased and for fair AI decisions, promoting ethical use, and preventing discrimi…</p> Signup and view all the answers

    What can bias in AI algorithms in CRM lead to?

    <p>What can bias in AI algorithms in CRM lead to?</p> Signup and view all the answers

    What is an example of ethical debt?

    <p>B. Launching an AI feature after discovering a harmful bias</p> Signup and view all the answers

    A consultant conducts a series of Consequence Scanning workshops to support testing diverse datasets. Which Salesforce Trusted AI Principles is being practiced>

    <p>B. Inclusivity</p> Signup and view all the answers

    A financial institution plans a campaign for preapproved credit cards? How should they implement Salesforce’s Trusted AI Principle of Transparency?

    <p>B. Flag sensitive variables and their proxies to prevent discriminatory lending practices.</p> Signup and view all the answers

    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?

    <p>A. Natural language processing</p> Signup and view all the answers

    What are the key components of the data quality standard?

    <p>B. Accuracy, Completeness, Consistency</p> Signup and view all the answers

    Which best describes the different between predictive AI and generative AI?

    <p>A. Predictive new and original output for a given input.</p> Signup and view all the answers

    Which type of bias imposes a system ‘s values on others?

    <p>A. Societal</p> Signup and view all the answers

    What is the rile of data quality in achieving AI business Objectives?

    <p>B. Data quality is required to create accurate AI data insights.</p> Signup and view all the answers

    What is a potential outcome of using poor-quality data in AI application?

    <p>B. AI models may produce biased or erroneous results.</p> Signup and view all the answers

    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?

    <p>B. Ethical AI Process Maturity Model</p> Signup and view all the answers

    Which data does Salesforce automatically exclude from Marketing Cloud Einstein engagement model training to mitigate bias and ethical risks?

    <p>B. Geographic</p> Signup and view all the answers

    How does a data quality assessment impact business outcome for companies using AI?

    <p>C. Provides a benchmark for AI predictions</p> Signup and view all the answers

    What is a key challenge of human AI collaboration in decision-making?

    <p>B. Creates a reliance on AI, potentially leading to less critical thinking and oversight</p> Signup and view all the answers

    A system admin recognizes the need to put a data management strategy in place. What is a key component of data management strategy?

    <p>B. Data Backup</p> Signup and view all the answers

    Study Notes

    Salesforce AI-Associate Exam Study Notes

    • Product Questions: 76 questions, Version 4.0
    • Exam: Salesforce Certified AI Associate
    • Resource: Questions and Answers (Retail Version - Full Questions Set)
    • Website: www.Justcerts.com

    Question 1

    • Benefit of a diverse, balanced, and large dataset: Model accuracy.
    • Explanation: A diverse dataset captures a variety of features and patterns for the Al task. A balanced dataset avoids overfitting or underfitting to a specific subset. A large dataset provides enough information for the model to learn and generalize to new data.

    Question 2

    • Common examples of Al in CRM: Predictive scoring, forecasting, and recommendations.
    • Explanation: Predictive scoring prioritizes leads, opportunities, and customers based on their likelihood to convert, churn, or buy. Forecasting anticipates future sales, revenue, or demand based on historical data and trends. Recommendations suggest optimal products, services, or actions based on customer preferences and behavior.

    Question 3

    • First step to prepare data for Al in CRM: Assessing data availability and quality.
    • Explanation: Determining data availability, storage location, access methods, and maintenance strategies are crucial before undertaking Al projects.

    Question 4

    • Role of data quality in medical diagnosis Al: Enhanced accuracy and reliability of predictions and diagnoses.
    • Explanation: Accurate, complete, consistent, and relevant data is critical for precise medical predictions, avoiding misdiagnosis and patient harm.

    Question 5

    • Ethical challenges in Al development: Potential for human bias in machine learning algorithms, lack of transparency in Al decision-making.
    • Explanation: Human bias can stem from training data, developer choices, or user interpretations. Lack of transparency makes it hard to understand and trust Al decisions.

    Question 6

    • Data quality dimension affected by inconsistent state/country values: Consistency.
    • Explanation: Consistent data values are uniform across records, fields, or sources, preventing confusion and errors in analyses.

    Question 7

    • Role of NLP in Al capabilities: Understanding and generating human language.
    • Explanation: NLP enables Al systems to process and understand human language through speech or text, aiding in analysis and interaction.

    Question 8

    • Salesforce Trusted Al Principle of Inclusivity example: Testing models with diverse datasets.
    • Explanation: Testing on diverse datasets ensures models are fair, unbiased, and representative of the target population.

    Question 9

    • Essential data quality dimension for custom service analytics application in Salesforce: Consistency.
    • Explanation: Data values must be uniform across records for the application to accurately and efficiently analyze cases.

    Question 10

    • Actions to ensure data quality for Al initiatives: Collect and curate high-quality data from reliable sources
    • Explanation: Relying on trustworthy and reliable sources ensures quality data for effective Al applications.

    Question 11

    • Einstein capability for Knowledge articles from emails: Generate.
    • Explanation: The Einstein Generate functionality automatically creates summaries and descriptions from relevant conversations.

    Question 12

    • Bias stemming from data labeled by stereotypes: Societal bias
    • Explanation: Societal biases reflect societal assumptions, norms, and values, potentially leading to unfair or skewed outcomes.

    Question 13

    • Example of an immutable trait per Salesforce: Financial status
    • Explanation: Financial status is considered an immutable trait because it's determined by factors outside an individual's control at birth, or inheritance, or economic conditions.

    Question 14

    • Impact of incomplete customer data quality on operations: Hindered accuracy of product recommendations.
    • Explanation: Incomplete data restricts AI’s ability to capture customer preferences and needs impacting the reliability of recommendations.

    Question 15

    • Key benefits of Al in improving CRM customer experiences: Streamlined case management, enhanced customer service and experience through categorizing and tracking customer support cases.
    • Explanation: Identifying topics, summarizing case resolutions, and providing automated customer interactions improve efficiency and reduces wait times.

    Question 16

    • Organization benefit from using Al to personalize shopping: Increased customer satisfaction.
    • Explanation: Al personalizes recommendations and offerings to meet customer preferences and needs boosting satisfaction.

    Question 17

    • Approach aligned with Salesforce's Trusted Al Principle of Inclusivity: Testing with diverse and representative datasets.
    • Explanation: Includes diverse, representative datasets to create fair and unbiased AI models, aligned with equitable representation of the target population or domain.

    Question 18

    • Data quality dimension affected due to inconsistent field type usages: Consistency.
    • Explanation: Consistent data values across all records are vital for accurate analyses; mixed field types impede this.

    Question 19

    • Mitigating potential AI bias: Implementing Salesforce's Trusted Al Principles.
    • Explanation: Adhering to Salesforce's Trusted Al Principles (Accountability, Fairness & Equality, Transparency, Privacy, etc.) minimizes the likelihood of AI bias.

    Question 20

    • Einstein features for enhancing sales: Opportunity Scoring, Lead Scoring, and Account Insights.
    • Explanation: AI-powered predictions for lead and opportunity likelihood of conversion through predictive models. Data insights on accounts, industry, location support effective selling strategies.

    Question 21

    • Cloud Kicks Al Model approach aligning with Salesforce's Inclusivity principle: Testing with diverse and representative datasets.
    • Explanation: Comprehensive dataset testing ensures models appropriately reflect the attributes, perspectives, and experiences of diverse groups, minimizing bias.

    Question 22

    • Focus of Salesforce's Accountability Principle: Taking responsibility for actions toward customers, partners, and society.
    • Explanation: Accountability requires awareness of ethical, legal, and regulatory standards for AI development and usage within organizations.

    Question 23

    • Sensitive variable liable to cause bias: Gender
    • Explanation: Gender is a sensitive variable as it can potentially lead to discriminatory categorization and treatment in AI systems if not handled properly.

    Question 24

    • Marketing manager Al solution: Einstein Engagement
    • Explanation: Ideal for optimizing email marketing campaigns, providing personalized recommendations and insights to improve customer engagement

    Question 25

    • Best field type for destination country: Picklist
    • Explanation: Guarantees consistency and accuracy in data entry by limiting the set of valid country options.

    Question 26

    • Customer information accessible for Al prediction rationale: Explanation of the prediction's rationale and a model card describing its creation
    • Explanation: A model card provides insight into the training and functioning of the AI model enhancing transparency.

    Question 27

    • Right of least privilege for data security: Limiting access based on required functions.
    • Explanation: Granting minimum necessary access prevents unauthorized data use or leakage.

    Question 28

    • Best method for customer data privacy: Tracking customer data consent preferences.
    • Explanation: Respecting and honoring customer choices regarding data handling fosters trust and compliance.

    Question 29

    • Key difference between generative and predictive Al: Generative Al creates new content based on existing data, predictive AI analyzes data.
    • Explanation: Generative AI produces novel outputs while predictive AI analyzes existing data to forecast future events or trends.

    Question 30

    • Key benefit of effective Al-human interaction: More informed and balanced decision making.
    • Explanation: Collaborative interaction between humans and AI leverage both parties’ strengths for improved insights and decision making.

    Question 31

    • Key characteristic of machine learning: Uses algorithms to learn from data and make decisions
    • Explanation: Machine learning algorithms analyze data patterns to improve decision-making/predictions, without explicit instructions.

    Question 32

    • Feature for removing duplicate customer records: Duplicate management
    • Explanation: Salesforce Duplicate Management tools find duplicates and handle them accordingly, improving data integrity.

    Question 33

    • Best Salesforce field type for preferred names: Text
    • Explanation: Allows flexible input of user-preferred names, capturing various formats and spellings.

    Question 34

    • Outcome of poor data quality: Biases in data become unintentionally learned and amplified by AI systems.
    • Explanation: Poor data quality leads to inaccurate or incomplete data, potentially introducing errors and bias into AI models, limiting their accuracy and usefulness.

    Question 35

    • Data type to avoid unintentional bias in AI: Demographic data
    • Explanation: Demographic data can include inherent biases and stereotypes leading to discriminatory practices or skewed insights.

    Question 36

    • Implication of user consent in regard to Al data privacy: Al infringes on privacy when user consent is not obtained.
    • Explanation: Al systems should not collect, use, or share data without explicit user consent aligning with relevant privacy regulations.

    Question 37

    • How does data quality enhance Al trustworthiness: High-quality data improves the reliability and credibility of Al-driven decisions, fostering trust amongst users.
    • Explanation: Data with high integrity (accuracy, completeness, consistence) in AI enables more reliable and trusted outcomes.

    Question 38

    • Identifying communication inefficiencies: Assessing data duplication in customer records to identify and resolve unnecessary sales contacts.
    • Explanation: Salesforce duplicate management tools identify and handle potential duplicate records and contacts, improving data quality and reducing communications inefficiencies.

    Question 39

    • Key factor for Al model training dataset selection: Dataset size.
    • Explanation: Datasets with adequate representation minimize bias while enabling AI models to fully comprehend and extrapolate patterns from the data.

    Question 40

    • Definition of machine learning: A data model used in Salesforce
    • Explanation: Datasets designed/structured with specific algorithms that learn and improve in accuracy over time, based on available data.

    Question 41

    • Einstein functionality for self-service issue resolution: Bots
    • Explanation: Natural Language Processing/Understanding (NLP/NLU) capabilities support conversational AI interfaces that customers can use for troubleshooting and guidance.

    Question 42

    • Critical concern when dealing with al and CRM data: Ensures compliance with laws and regulations.
    • Explanation: Data privacy is essential to comply with local/global requirements governing data handling.

    Question 43

    • Developing trusted AI with Salesforce: Creating guardrails that mitigate toxicity and protect personally identifiable information (PII)
    • Explanation: Implementing measures to prevent unethical/biased AI and to safeguard confidential data are critical for trusted AI solutions.

    Question 44

    • Potential AI training data bias source: Skewed data toward particular demographic or source.
    • Explanation: Datasets may not represent the true diversity or range of the target population due to sampling bias or limitations.

    Question 45

    • Salesforce Trust Al Principle of Empowerment goal: Empower users of all skill levels to build Al applications without extensive technical expertise.
    • Explanation: AI tools enable creation of more and wider access to AI capabilities, promoting user and developer efficiency in using AI capabilities.

    Question 46

    • Assessing data quality for Al tasks: Leverage data apps from AppExchange.
    • Explanation: Commercial solutions provide tools for comprehensive data quality evaluation and management.

    Question 47

    • Preventing bias in AI systems during training: Import diverse training data
    • Explanation: Using comprehensive datasets with representation from various groups ensures that models aren’t skewed towards limited perspectives.

    Question 48

    • Key consideration for data quality in AI implementation: Data's role in training and fine-tuning Salesforce’s AI models
    • Explanation: Data quality directly affects the effectiveness of AI model training and refinement processes due to dependence on the dataset quality.

    Question 49

    • Al capacity for enhancing sales & customer support: Einstein Lead Scoring and Case Classification
    • Explanation: Prioritizes leads based on conversion likelihood, categorizes instances, and routes requests based on characteristics using automated AI-driven systems.

    Question 50

    • Salesforce Honesty Guideline in AI training: Ensure appropriate consent and transparency when using Al-generated responses.
    • Explanation: Al outcomes should be ethically responsible and respectful of data users’ rights.

    Question 51

    • Benefits of data quality & transparency on Al bias: Reduce the chances of bias.
    • Explanation: Accurate and transparent data mitigate biases embedded in data.

    Question 52

    • Al application to improve sales & customer support: Lead scoring, opportunity forecasting, and case classification.
    • Explanation: This enables prioritized lead management, accurate sales projections, and proper case routing accordingly.

    Question 53

    • Reason for inaccurate Al predictions: Poor data quality
    • Explanation: Inaccurate, incomplete, inconsistent data creates skewed predictions and questionable results.

    Question 54

    • Required feature to ensure email address in new contact records: Validation rule.
    • Explanation: Data validation (email address) ensures data consistency and completeness in new contact entries, while maintaining data quality.

    Question 55

    • Data quality dimension affected by inconsistent field usages: Consistency
    • Explanation: Inconsistent data formats (text vs picklist in this case) can lead to errors in analyses and inaccurate inferences.

    Question 56

    • Essential data quality for Al shoe demand predictions: Reliability
    • Explanation: Reliable data (trustworthy and consistent) enables more accurate and dependable predictions.

    Question 57

    • Best Al application for improving sales processes: Lead scoring and opportunity forecasting.
    • Explanation: AI-driven lead scoring prioritizes potentially valuable leads, and forecasting improves sales projections based on past data.

    Question 58

    • Al’s role in understanding customer interactions: Providing call summaries.
    • Explanation: Natural language processing (NLP) in AI transcribes and summarizes interactions, providing insights in an organized format to sales representatives.

    Question 59

    • High data quality impact on customer relations: Increased brand loyalty
    • Explanation: Data quality enhances accuracy and relevance of communications/product/service offerings, improving customer trust and loyalty.

    Question 60

    • Role of Salesforce Trusted Al principles: Guiding ethical and responsible Al use.
    • Explanation: Responsible Al development, promoting trust and avoiding ethical/legal pitfalls.

    Question 61

    • Data quality role in ethical use of Al: High-quality data is essential for ensuring unbiased and fair decisions and promoting responsible AI use, avoiding bias.
    • Explanation: High-quality data, free from biases, promotes fair and unbiased Al outputs minimizing discrimination and ethical considerations

    Question 62

    • Potential outcomes of AI algorithm bias in CRM: Ethical challenges
    • Explanation: Bias affects fairness, perception, and treatment within CRM/customer relationship management systems, leading to potentially discriminatory or adverse outcomes.

    Question 63

    • Example of ethical debt: Launching an Al feature after discovering a harmful bias
    • Explanation: Unfair/biased outcomes or features, identified late, create ethical debt in deploying AI solutions.

    Question 64

    • Salesforce Trusted Al Principle: Inclusivity
    • Explanation: The consistent application of consequence scanning ensures diverse testing, promoting AI solutions that represent diverse perspectives, leading to higher trust.

    Question 65

    • Implementing Transparency in Al by financial institutions: Flag sensitive variables and their proxies to prevent discriminatory lending practices
    • Explanation: This prevents discrimination by identifying and separating relevant criteria ensuring fairness in lending processes.

    Question 66

    • Appropriate AI for chatbot implementation: Natural language processing
    • Explanation: NLP is an appropriate AI technique for chatbots, enabling natural language understanding and response generation, to engage in conversational interactions with customers.

    Question 67

    • Key components of data quality standards: Accuracy, Completeness, Consistency
    • Explanation: These elements form a benchmark/measuring stick for evaluating and maintaining quality standards in a data set enabling accurate and reliable AI processing.

    Question 68

    • Difference between predictive and generative Al: Predictive AI uses machine learning to classify or predict output from input data, generative AI does not use machine learning to generate its outputs
    • Explanation: Predictive AI is driven by analyzing past data to forecast trends, while generative AI creates new outputs.

    Question 69

    • Type of bias in values imposition: Societal bias
    • Explanation: This type of bias involves the enforcement or expectation of predefined values or judgment in AI systems that are not universally applicable across cultures.

    Question 70

    • Data quality role for achieving Al objectives: Data quality is essential for achieving accurate Al data insights.
    • Explanation: Accurate data is crucial in AI for achieving trustworthy and realistic AI outputs and to support various business goals properly.

    Question 71

    • Outcome of poor data quality in Al applications: AI models produce biased or erroneous results.
    • Explanation: Data quality directly impacts the model, with poor-quality data having a direct effect on its accuracy and reliability, and its ability to deliver unbiased results.

    Question 72

    • Ethical AI Model for guiding AI development: Ethical Al Process Maturity Model
    • Explanation: A comprehensive framework for assessing and improving ethical AI practices throughout development steps.

    Question 73

    • Data excluded from training AI models: Geographic data.
    • Explanation: Models are trained on non-geographic data to avoid potential bias or discrimination related to location or geography.

    Question 74

    • Data quality's impact on business outcomes: Provides benchmark/measuring stick for Al predictions.
    • Explanation: Accurate, consistent data enables reliable AI outputs.

    Question 75

    • Key challenge in human Al decision-making collaboration: Reliance on Al, potentially leading to less critical thinking and oversight.
    • Explanation: Over-reliance on the accuracy and output of AI systems, may lead to a reduced critical engagement with information.

    Question 76

    • Key component of data management strategy: Data Backup
    • Explanation: Essential for data security and/or disaster recovery by creating backup copies of data in separate locations or devices.

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    Salesforce Certified AI Associate Exam PDF

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    Prepare for the Salesforce Certified AI Associate exam with these comprehensive study notes. This resource covers product questions and essential concepts like dataset diversity and common AI applications in CRM. Enhance your understanding and boost your exam readiness.

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