AI Associate Practice Test 13 — 15 Questions

Question 1

A support agent needs to quickly find a relevant knowledge article while handling a case. Which Einstein feature suggests articles automatically?

Accepted Answer

Einstein Article Recommendations. Einstein Article Recommendations suggests knowledge articles to agents based on the case details.

Answer

Einstein Next Best Action

Answer

Einstein Recommendation Builder

Answer

Einstein Case Classification

Question 2

An admin wants to create a prompt template that dynamically pulls the case subject and description to generate a knowledge article draft. Which prompt template type should they use in Prompt Builder?

Accepted Answer

Field Generation. Field Generation prompt templates are used to generate content for a specific field, such as a knowledge article draft.

Answer

Sales Email

Answer

Service GPT Reply Recommendation

Answer

Flex Prompt

Question 3

A healthcare organization uses Salesforce to develop an AI model for patient readmission prediction. They must comply with HIPAA regulations. The dataset includes patient names, addresses, medical record numbers, and detailed clinical notes. The data scientist plans to train a supervised model using historical readmission outcomes. What is the most important data governance step before model training?

Accepted Answer

De-identify all protected health information (PHI) by removing or masking identifiers.. HIPAA mandates that protected health information (PHI) must be de-identified before it can be used for model training without patient authorization. Removing or masking identifiers such as names, addresses, and medical record numbers ensures the dataset no longer contains individually identifiable information, allowing the organization to comply with the HIPAA Privacy Rule while still using clinical notes for predictive modeling.

Answer

Use only aggregated data that does not include any patient-level details.

Answer

Obtain written patient consent for every record used in training.

Answer

Store the data in a separate, encrypted environment with access controls.

Question 4

An organization uses Einstein Conversation Insights to analyze sales call recordings. They want to automatically capture next steps discussed during calls and log them as tasks in Salesforce. Which feature should they use?

Accepted Answer

Einstein Conversation Insights. Einstein Conversation Insights can capture next steps from call recordings and create tasks automatically. The other options are not designed for extracting action items from audio.

Answer

Einstein Email Insights

Answer

Einstein Activity Capture

Answer

Einstein Prediction Builder

Question 5

A sales rep wants Einstein to automatically capture emails and calendar events to Salesforce without manual logging. Which feature enables this?

Accepted Answer

Einstein Activity Capture. Einstein Activity Capture automatically logs emails and events to Salesforce records based on sync settings.

Answer

Einstein Email Insights

Answer

Einstein Conversation Insights

Answer

Einstein GPT for Sales

Question 6

Before training an Einstein Prediction model, a data analyst must perform data quality checks. Which THREE checks are most critical?

Accepted Answer

Remove duplicate records that could cause data leakage. Duplicate records can cause data leakage by allowing the model to see the same or highly similar data in both training and validation splits, leading to overfitting and inflated performance metrics. Removing duplicates ensures that the model generalizes to unseen data rather than memorizing repeated instances.

Answer

Confirm that label distribution matches the target baseline

Answer

Ensure all features follow a normal distribution

Question 7

Refer to the exhibit. An admin configures Einstein Next Best Action with the above JSON. The expected behavior is to recommend the top 5 actions for open leads with a score of at least 70. However, only 2 recommendations appear for some leads. Which is the most likely cause?

Accepted Answer

The scoreThreshold of 70 excludes many actions, so fewer than 5 meet the criteria.. The scoreThreshold of 70 filters out any actions with a score below 70. If fewer than 5 actions meet this threshold, the system returns only those that qualify, resulting in fewer than 5 recommendations. The maxRecommendations setting defines the upper limit, but the actual number returned is constrained by the scoreThreshold.

Answer

The filter on Lead Status is incorrectly excluding actions.

Answer

The recommendation strategy is misconfigured for this object.

Answer

The maxRecommendations is set to 2 instead of 5.

Question 8

For a real-time AI application that requires low-latency access to customer interaction data, which storage solution is most appropriate?

Accepted Answer

In-memory data store.. In-memory data stores (e.g., Redis, Memcached) store data in RAM rather than on disk, providing sub-millisecond read/write latencies essential for real-time AI applications that need immediate access to customer interaction data. This eliminates disk I/O bottlenecks and enables high-throughput, low-latency data retrieval for time-sensitive inference or decision-making.

Answer

Flat files on a network drive.

Answer

Relational database with complex joins.

Answer

Data lake with batch processing.

Question 9

A nonprofit organization uses Salesforce to manage donor relationships. They have implemented Einstein Prediction Builder to predict which donors are likely to upgrade their donation level in the next 90 days. The model was built using a custom object "Donation" with fields like Amount, Frequency, and Campaign. After deployment, the predictions seem random and do not correlate with donor engagement. The admin suspects the model is not trained on enough records. The organization has 500 donors with at least two donations each. What should the admin do to improve the model?

Accepted Answer

Ensure that at least 500 records exist where the donor actually upgraded, and retrain the model.. Einstein Prediction Builder requires a minimum number of positive outcome records (upgrade events) to train a reliable model. With only 500 donors and likely far fewer upgrades, the model lacks sufficient signal. Ensuring at least 500 actual upgrade records provides the necessary positive examples for the algorithm to learn meaningful patterns, reducing randomness in predictions.

Answer

Increase the prediction window from 90 to 180 days to capture more upgrade events.

Answer

Use a different field as the prediction outcome, such as 'donation amount increase'.

Answer

Add more fields to the model, such as donor age and geographic location.

Question 10

A global retail company deploys an AI-powered chatbot for customer service. The chatbot uses natural language processing to understand and respond to customer inquiries. After deployment, the company notices that the chatbot consistently provides less accurate and less helpful responses to customers from non-English-speaking regions, particularly those using dialects or slang. The company's data science team trained the model primarily on English-language customer service transcripts from the US and UK. The AI Ethics team has raised concerns about fairness and potential bias. The company wants to address this issue while maintaining overall performance and minimizing cost. Which action should the company take first?

Accepted Answer

Conduct a fairness audit using diverse test cases from multiple languages and dialects to quantify the disparity.. The first step in addressing potential bias in an AI system is to measure and quantify the disparity. Conducting a fairness audit with diverse test cases from multiple languages and dialects provides the data science team with a clear, empirical baseline of the model's performance gaps. This diagnostic step is essential before any remediation (like retraining or adding constraints) to ensure that subsequent actions are targeted and effective, avoiding wasted resources or unintended consequences.

Answer

Implement a fairness constraint in the model's loss function to penalize disparities across language groups.

Answer

Disable the chatbot for non-English languages and redirect those customers to human agents.

Answer

Collect more training data from all regions and retrain the model from scratch.

Question 11

You are a Salesforce AI Specialist at a mid-sized manufacturing company. The company uses Einstein Lead Scoring to prioritize leads. The model was trained on historical lead data and has been in production for three months. Recently, the sales team reports that high-scoring leads are not converting as expected. You investigate and find that the model's data source includes leads from the past 18 months. However, six months ago, the company changed its lead qualification process: they started requiring a demo before scoring leads as 'qualified.' As a result, the definition of a converted lead changed. What is the best course of action to improve model performance?

Accepted Answer

Retrain the model using only leads from the last six months after the process change. The change in lead qualification process six months ago introduced a data distribution shift (concept drift), making older leads no longer representative of the current conversion behavior. Retraining the model on only the last six months of data aligns the training set with the new definition of a 'converted lead,' allowing Einstein Lead Scoring to learn the updated patterns and improve prediction accuracy.

Answer

Manually adjust the model's prediction threshold to account for the new process

Answer

Remove the 'Demo Scheduled' field from the model to avoid bias

Answer

Add more historical leads from before the process change to increase data volume

Question 12

Which Salesforce AI feature provides automated statistical analysis and generates plain-language stories about trends in data?

Accepted Answer

Einstein Discovery. Einstein Discovery automatically analyzes data and produces stories, charts, and improvement suggestions.

Answer

Einstein Forecasting

Answer

Einstein Prediction Builder

Answer

Einstein GPT

Question 13

A marketing team wants to recommend products and content to website visitors in Experience Cloud. Which Einstein feature should they use?

Accepted Answer

Einstein Recommendation Builder. Einstein Recommendation Builder is designed for product/content recommendations in Experience Cloud.

Answer

Einstein Article Recommendations

Answer

Einstein Next Best Action

Answer

Einstein Prediction Builder

Question 14

A Salesforce admin wants to use Einstein Prediction Builder to predict case resolution time. What type of data is most critical for training this model?

Accepted Answer

Historical case records including resolution time. Einstein Prediction Builder requires historical data with known outcomes to train a supervised machine learning model. Historical case records containing actual resolution times provide the labeled examples needed for the model to learn patterns and predict future case resolution times. Without this ground truth data, the model cannot be trained to make accurate predictions.

Answer

Customer satisfaction survey responses

Answer

Product inventory levels

Answer

Employee work schedules

Question 15

A company is building an Agentforce agent to handle order cancellations. Which THREE components are essential to configure in Agent Builder? (Choose three.)

Accepted Answer

Topics (e.g., 'Cancel Order'). Agentforce requires defining topics, actions, and testing within Agent Builder.

Answer

Intents and entities for NLP

Answer

Prompt Builder template