50 AI Associate Practice Questions: Question Bank 2025

What is the primary purpose of implementing bias detection in AI systems?

A sales team wants to use Einstein to predict which leads are most likely to convert. Which Salesforce AI feature should they implement?

Which data quality characteristic is MOST critical for training accurate AI models?

A retail company wants to implement an AI solution to provide personalized product recommendations to customers on their website. What is the FIRST step they should take?

Which ethical principle requires that AI systems provide clear explanations about how they arrive at decisions?

A company is experiencing poor performance from their Einstein prediction model. Upon investigation, they discover that 95% of their training data represents one outcome while only 5% represents the alternative. What is the primary issue?

An organization wants to use Einstein Bots to handle customer service inquiries. Which consideration is MOST important for ensuring the bot provides accurate responses?

A healthcare organization is implementing an AI system to assist with patient diagnosis. Which approach BEST demonstrates responsible AI governance?

A financial services company needs to implement an AI model that complies with regulations requiring them to explain every automated decision to customers. Their data science team proposes using a complex deep learning ensemble model with superior accuracy but limited interpretability, versus a simpler decision tree model with slightly lower accuracy but clear explainability. Considering regulatory requirements and ethical AI principles, which approach should they prioritize?

A manufacturing company has implemented Einstein Analytics to predict equipment failure. After six months, they notice the model's accuracy has significantly degraded. Historical data shows that the company recently upgraded 40% of their machinery to newer models with different sensor configurations. What is the MOST likely cause of the degradation, and what should be done?

A financial services company wants to use AI to analyze customer data but must comply with strict data residency requirements. Which principle should guide their AI implementation strategy?

What is the primary purpose of feature engineering in preparing data for AI models?

A retail company is implementing Einstein Prediction Builder to forecast customer churn. They have historical data spanning 5 years, but recent business model changes occurred 6 months ago. What data strategy should they adopt?

Which Salesforce Einstein feature would be most appropriate for automatically suggesting the next best product to offer a customer based on their purchase history and similar customer behaviors?

A healthcare organization is concerned about AI bias in their patient triage system. During testing, they discover the system consistently assigns lower priority scores to certain demographic groups. What is the most likely root cause?

What is the relationship between precision and recall in evaluating AI model performance?

A company wants to ensure their AI model remains accurate over time as business conditions change. What practice should they implement?

What does 'data quality' mean in the context of preparing data for AI models?

A sales team wants to use Einstein Opportunity Scoring to prioritize deals, but they notice the scores don't align with their experienced sales managers' intuition. What should be the first troubleshooting step?

An organization is implementing AI-powered customer service automation. They want to ensure transparency with customers about AI usage. Which approach best demonstrates ethical AI deployment?

A sales manager wants to use Einstein to predict which opportunities are most likely to close. Which data quality practice is MOST important for improving prediction accuracy?

What is the primary purpose of establishing a data governance framework before implementing AI solutions in Salesforce?

A healthcare company is implementing AI-powered case classification in Salesforce. Which ethical consideration should be their PRIMARY concern when designing the solution?

An organization notices that their AI-powered lead scoring model consistently assigns lower scores to leads from certain geographic regions, despite similar qualification criteria. What type of AI issue does this represent?

A company wants to use Einstein Next Best Action to recommend products to customers. Their product catalog data is stored in an external system and updated daily. What is the BEST approach to ensure Einstein has access to current product information?

When implementing Einstein Bots, what is the recommended approach for handling conversations that the bot cannot resolve?

A financial services company is evaluating Einstein Discovery for analyzing customer investment patterns. They have data in multiple Salesforce objects with complex relationships. What data preparation step is MOST critical before building models?

An organization wants to understand why their Einstein Prediction model recommended a specific outcome for a particular case. Which AI principle does this requirement reflect, and what Salesforce capability addresses it?

A retail company using Einstein Recommendations notices that the system only suggests products customers have already purchased. What is the MOST likely root cause of this issue?

What is the primary difference between supervised and unsupervised machine learning in the context of Salesforce AI features?

A healthcare organization is implementing AI to analyze patient data and wants to ensure compliance with ethical guidelines. Which principle should be their PRIMARY consideration when developing the AI system?

A sales team wants to use Einstein Lead Scoring in Salesforce. What is the MINIMUM requirement for the AI model to begin generating meaningful predictions?

What is the primary purpose of data normalization in preparing datasets for AI model training?

A retail company notices that their AI recommendation engine consistently suggests products that were popular 6 months ago but are no longer in demand. What is the MOST likely cause of this issue?

Which scenario represents an example of algorithmic bias that violates ethical AI principles?

A financial services company wants to implement Einstein Next Best Action to provide personalized recommendations to customers. Which Salesforce feature must be configured FIRST to enable this functionality?

A data scientist discovers that 40% of the values in a critical feature column are missing. What is the BEST approach to handle this missing data before training an AI model?

What is the primary difference between supervised and unsupervised learning in AI?

A manufacturing company wants to use AI to predict equipment failures before they occur. They have sensor data from machines including temperature, vibration, and pressure readings collected every minute for the past 3 years. Which type of AI use case does this represent?

An organization is implementing AI-powered decision-making systems and wants to ensure transparency. Which practice BEST supports the principle of explainable AI (XAI)?

A sales manager wants to understand how Einstein Lead Scoring assigns scores to leads in Salesforce. What is the PRIMARY factor that determines lead scores?

A healthcare organization is implementing AI to analyze patient data and must comply with HIPAA regulations. Which data governance practice is MOST critical when preparing data for AI model training?

What is the primary purpose of implementing explainable AI (XAI) techniques in machine learning models?

A retail company wants to use AI to predict customer churn. Their dataset contains 100,000 customers, but only 2% have actually churned. What data challenge does this represent, and what is the recommended approach?

A company implements an AI chatbot for customer service. After deployment, they notice the chatbot performs poorly for non-English speakers even though it was advertised as multilingual. What ethical AI principle has likely been violated?

An insurance company wants to implement Einstein Next Best Action in Salesforce to recommend personalized offers to customers. What is a prerequisite for this implementation?

What is the difference between supervised and unsupervised learning in machine learning?

A financial services company is building a credit risk assessment AI model. During testing, they discover the model consistently assigns lower credit scores to applicants from certain zip codes, which correlates with racial demographics. What should be the FIRST step in addressing this issue?

A manufacturing company wants to implement predictive maintenance using AI to predict equipment failures. They have sensor data collected every second from 500 machines over 5 years. What data preparation challenge are they MOST likely to face?

A B2B company implements Einstein Opportunity Scoring in Salesforce. Sales representatives report that the AI scores don't align with their intuition about which deals will close. The AI model was trained on 3 years of historical opportunity data. What is the MOST likely reason for this disconnect?