Salesforce AI Fundamentals Quiz
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Questions and Answers

Which Salesforce Trusted AI Principle is demonstrated by conducting Consequence Scanning Workshops to test diverse datasets?

  • Accountability
  • Reliability
  • Inclusivity (correct)
  • Transparency

Which Einstein capability is used to create content for Knowledge articles through emails?

  • Analyze
  • Predict
  • Discover
  • Generate (correct)

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

  • Enhancing the efficiency of decision processes
  • Eliminating human biases completely
  • Reducing the complexity of decisions
  • Balancing human intuition with AI analysis (correct)

Which principle focuses on ensuring fairness by involving various stakeholders in AI development?

<p>Inclusivity (C)</p> Signup and view all the answers

What aspect of decision-making does AI primarily aim to support rather than replace?

<p>Human judgment (C)</p> Signup and view all the answers

Which of the following best encapsulates the focus of the Transparency principle in AI?

<p>Ensuring stakeholders understand AI workings (D)</p> Signup and view all the answers

Which AI principle emphasizes the responsibility of developers to mitigate potential harms?

<p>Accountability (C)</p> Signup and view all the answers

Which of the following capabilities best describes the predictive functions of AI?

<p>Forecasting future trends (A)</p> Signup and view all the answers

What is the consequence of launching an AI feature after discovering a harmful bias?

<p>Potential for legal issues (C)</p> Signup and view all the answers

What should a marketing manager prioritize to enhance customer engagement with AI?

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

What type of bias reflects societal values that may influence a system's outcomes?

<p>Societal (C)</p> Signup and view all the answers

What is a potential consequence of violating data privacy laws?

<p>Significant financial penalties (A)</p> Signup and view all the answers

What is a common strategy for improving an AI data model before a product launch?

<p>Delaying the launch to retrain the model (D)</p> Signup and view all the answers

Which functionality best helps in optimizing marketing journeys using AI?

<p>Journey Optimization (B)</p> Signup and view all the answers

Which bias occurs when a system reflects only the data it has been trained on, rather than broader societal values?

<p>Algorithmic bias (D)</p> Signup and view all the answers

What is the best response to discovering a harmful bias in an AI model before product release?

<p>Retrain the AI data model (A)</p> Signup and view all the answers

What is a key component of a data management strategy?

<p>Naming Convention (B)</p> Signup and view all the answers

What feature should a data quality expert use to ensure each new contact has an email address or phone number?

<p>Validation rule (B)</p> Signup and view all the answers

Which of the following best explains the purpose of a validation rule?

<p>To enforce data integrity (C)</p> Signup and view all the answers

Which component is NOT typically part of a data management strategy?

<p>Color Coding (A)</p> Signup and view all the answers

What is a characteristic of predictive AI?

<p>Analyzes historical data (B)</p> Signup and view all the answers

Which of the following is an example of generative AI?

<p>Art generation software (B)</p> Signup and view all the answers

What is the main goal of implementing a data backup strategy?

<p>Prevent data loss in emergencies (B)</p> Signup and view all the answers

Which concept refers to the ability of a system to ensure the accuracy of data over time?

<p>Data quality management (A)</p> Signup and view all the answers

Which application of AI would be most beneficial for a sales manager looking to improve processes in Salesforce?

<p>Lead scoring and opportunity forecasting (C)</p> Signup and view all the answers

What is a potential consequence of bias in AI algorithms within CRM systems?

<p>Ethical challenges in CRM systems (C)</p> Signup and view all the answers

How can AI enhance lead scoring in a sales environment?

<p>By analyzing multiple data points for better prioritization (A)</p> Signup and view all the answers

In Salesforce, which feature would directly utilize AI for opportunity forecasting?

<p>Predictive analytics tools (A)</p> Signup and view all the answers

What aspect of AI can help prevent ethical challenges in CRM systems?

<p>Implementing transparent data usage policies (A)</p> Signup and view all the answers

What role does data modeling play in improving a sales team's performance?

<p>It identifies trends and patterns in customer behavior (B)</p> Signup and view all the answers

Which of the following is NOT a benefit of using AI in CRM?

<p>Elimination of all manual tasks (B)</p> Signup and view all the answers

What could lead to unintended consequences if AI algorithms in CRM are biased?

<p>Misrepresentation of customer demographics (D)</p> Signup and view all the answers

Which AI application is best suited for improving lead evaluation?

<p>Opportunity forecasting (D)</p> Signup and view all the answers

What purpose do machine learning models serve in enhancing sales processes?

<p>To predict future sales trends (A)</p> Signup and view all the answers

Which of the following is an AI application that aids in classifying customer cases?

<p>Case classification (B)</p> Signup and view all the answers

What is the primary benefit of opportunity forecasting in sales?

<p>Providing accurate lead assessments (A)</p> Signup and view all the answers

In what way can AI improve customer support processes?

<p>By using chatbots for immediate responses (D)</p> Signup and view all the answers

Which AI application helps analyze historical sales data to guide future strategies?

<p>Predictive analytics (B)</p> Signup and view all the answers

What function does data governance serve in customer interactions?

<p>To ensure data quality and compliance (D)</p> Signup and view all the answers

Which aspect is NOT typically enhanced by using AI in sales?

<p>Sales team reliability (C)</p> Signup and view all the answers

Flashcards

Inclusivity

The principle emphasizes the importance of involving diverse stakeholders throughout the AI development process to ensure fairness and prevent bias.

Transparency

The key focus of the Transparency principle in AI is making sure that all stakeholders understand how the AI system works and how it makes decisions.

Accountability

It involves the responsibility of developers to take necessary actions to minimize or prevent potential harm caused by their AI systems.

Predictive AI

The AI system's ability to predict future trends and patterns based on historical data is a crucial aspect of its functionality.

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Societal Bias

It describes the bias that arises when an AI system's training data reflects existing societal values, potentially leading to biased outcomes.

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Algorithmic Bias

It refers to the bias that occurs when an AI system's decisions reflect the specific data it was trained on, rather than broader societal values.

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Naming Convention

Data management strategy includes various components, including naming conventions, which help organize and manage data in a consistent and efficient manner.

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Validation Rule

Validation rules are designed to enforce data integrity by ensuring that all new contacts have either an email address or a phone number.

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Data integrity

Validation rules play a crucial role in maintaining data integrity by enforcing rules that ensure the accuracy and consistency of data within a system.

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Predictive AI

Predictive AI utilizes machine learning algorithms and statistical analysis to analyze historical data and predict future trends, providing insights into potential outcomes.

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Generative AI

Generative AI is a type of AI that focuses on creating new content, such as text, images, audio, or videos, based on its training data.

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Data backup strategy

The main goal of implementing a data backup strategy is to ensure data protection and prevent data loss in case of emergencies, such as system failures or natural disasters.

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Data Quality Management

Data quality management is essential for ensuring that data remains accurate, complete, and consistent over time. It involves processes and techniques for improving data quality.

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Lead scoring and opportunity forecasting

AI applications can be highly beneficial for sales managers, particularly lead scoring and opportunity forecasting, which help prioritize leads and predict potential sales.

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Lead scoring

AI-powered lead scoring analyzes multiple data points to create a more accurate and comprehensive evaluation of leads, helping sales teams prioritize their efforts effectively.

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Opportunity forecasting

AI algorithms in CRM systems can analyze historical and real-time data to predict the likelihood of closing an opportunity, providing insights into potential sales outcomes.

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Data modeling

Data modeling plays a crucial role in understanding customer behavior and predicting future trends, allowing sales teams to tailor their strategies to different customer segments and improve their performance.

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Chatbots for customer support

AI-powered chatbot systems can provide immediate responses to customer inquiries, reducing wait times and improving customer satisfaction.

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Predictive analytics in sales

Predictive analytics utilizes historical sales data and AI algorithms to identify trends and patterns, allowing sales teams to make more informed decisions and optimize future strategies.

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Data governance in customer interactions

Data governance is essential for ensuring that customer data is used ethically and responsibly, complying with relevant regulations and maintaining data quality.

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Case classification in customer support

AI-powered case classification systems analyze customer case descriptions and categorize them into specific types, helping support agents quickly address the issues.

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Opportunity forecasting

Opportunity forecasting aims to predict the probability of converting leads into paying customers, providing a more accurate estimate of future sales revenue.

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AI in customer support

AI can improve customer support by automating repetitive tasks and providing immediate responses through chatbots, freeing up human agents for more complex issues.

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Chatbots

AI-powered chatbots are designed to provide immediate responses to customer inquiries, offering a more efficient and personalized customer experience.

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Data governance

Data governance plays a crucial role in ensuring that customer data is handled ethically and responsibly, complying with regulations and maintaining data quality.

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Consequence of harmful bias

The launch of an AI feature after discovering a harmful bias can lead to significant legal issues, as it raises concerns about fairness and discrimination.

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Einstein Engagement

Einstein Engagement is a Salesforce feature specifically designed to enhance customer engagement using AI, by providing personalized experiences and leveraging data insights.

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Addressing harmful bias

The most effective response to discovering a harmful bias in an AI model before product release is to retrain the AI data model, ensuring that it learns from a more inclusive dataset.

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Data Quality Management

Data quality management involves processes and techniques for improving the accuracy, consistency, and completeness of data within a system.

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Ethical AI in CRM

AI algorithms in CRM systems strive to prevent ethical challenges by implementing transparent data usage policies and prioritizing fair and unbiased treatment of customers.

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Machine learning in sales

Machine learning models in sales processes help predict future sales trends by analyzing historical data and identifying patterns in customer behavior, enabling sales teams to make more informed decisions.

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Study Notes

AI Fundamentals

  • Salesforce Certified AI Associate is a professional certification awarded by Salesforce
  • To improve sales processes using AI in Salesforce, sales managers can use lead scoring and opportunity forecasting
  • Applications of AI in Salesforce lead to ethical challenges
  • AI algorithms can be biased which may lead to ethical challenges in CRM systems
  • Data management strategy has a key component: Naming convention
  • To ensure every new contact contains at least an email address or a phone number, use validation rule
  • Predictive AI uses data patterns to predict future outcomes, Generative AI creates new data based on existing data
  • When testing diverse datasets, use Consequence Scanning Workshops to support the Inclusivity Salesforce Trusted AI Principle
  • Discover is an Einstein Capability to create Knowledge content using emails

AI Capabilities in CRM

  • Einstein Engagement functionality is used by marketing managers to better engage customers

Ethical Considerations of AI

  • A key challenge of human-AI collaboration in decision-making is reducing human involvement in decision-making processes
  • Societal bias imposes a system's values on others

Data for AI

  • To enhance sales processes and customer support, business analysts can use lead scoring, opportunity forecasting, and case classification

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Related Documents

Salesforce Certified AI Associate PDF Exam Paper

Description

Test your knowledge on Salesforce Certified AI Associate topics, including lead scoring, opportunity forecasting, and the ethical challenges of AI in CRM systems. Dive into AI capabilities like Einstein Engagement and learn about effective data management strategies in sales.

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