AI Associate Practice Test 42 — 15 Questions

Question 1

A sales team notices that their lead scoring model assigns high scores to leads that rarely convert. The model was trained on data from the past 5 years. What is the most likely cause?

Accepted Answer

There is concept drift because buying behaviors have changed. Concept drift occurs when the relationship between features and labels changes over time. Old data may no longer represent current sales patterns.

Answer

The features used are irrelevant to lead conversion

Answer

The model is overfitting to noise in the training data

Answer

The model is underfitting and needs more features

Question 2

A company wants to automatically extract key information like order numbers and dates from customer emails. Which NLP technique should be used?

Accepted Answer

Entity extraction. Entity extraction (named entity recognition) identifies specific pieces of information such as dates, order numbers, and names from text.

Answer

Sentiment analysis

Answer

Text classification

Answer

Text summarization

Question 3

A customer support center wants to automatically route incoming cases to the appropriate department based on the issue description. Which NLP task is most relevant?

Accepted Answer

Text classification. Text classification assigns a category (e.g., billing, technical) to a text, enabling automated routing.

Answer

Intent detection

Answer

Entity extraction

Answer

Sentiment analysis

Question 4

What is the primary difference between narrow AI and general AI?

Accepted Answer

Narrow AI is task-specific; general AI can perform any intellectual task a human can. Narrow AI is designed for specific tasks, while general AI (AGI) would have human-like broad capabilities, which does not yet exist.

Answer

Narrow AI can perform any intellectual task; general AI is limited to one task

Answer

Narrow AI uses machine learning; general AI uses deep learning

Answer

General AI is already deployed in CRM systems; narrow AI is experimental

Question 5

A data scientist is building a churn prediction model. The dataset has 95% non-churn and 5% churn. Which THREE actions should the data scientist take to address the class imbalance?

Accepted Answer

Undersample the non-churn class. Oversampling minority class, undersampling majority class, and using appropriate metrics (like precision/recall) are common approaches. Using accuracy is not recommended. Training on original data without adjustment will produce a biased model.

Answer

Train the model on the original dataset without changes

Answer

Use accuracy as the primary metric

Question 6

A company’s AI model recommends products to customers. The team wants to measure how often the recommended products are actually purchased. Which metric is most appropriate?

Accepted Answer

Precision. Precision measures the proportion of recommended items that are relevant (purchased). For product recommendations, precision is key.

Answer

F1 score

Answer

Recall

Answer

Accuracy

Question 7

A sales director wants to implement lead scoring but has no historical data on which leads converted. What approach can the team use to start?

Accepted Answer

Use unsupervised learning to cluster leads into segments and score based on cluster characteristics. Unsupervised learning can cluster leads based on similarities, providing initial scores without labeled outcomes.

Answer

Train a supervised model using assumptions as labels

Answer

Skip lead scoring until enough conversion data is collected

Answer

Use reinforcement learning to learn scoring from sales team feedback

Question 8

Which type of machine learning is used when a model is trained on historical sales data that includes both input features and the known outcome (e.g., closed won/lost) to predict whether a new lead will convert?

Accepted Answer

Supervised learning. Supervised learning uses labeled training data where the correct output is provided. Lead scoring with historical outcomes is a classic supervised learning task.

Answer

Semi-supervised learning

Answer

Reinforcement learning

Answer

Unsupervised learning

Question 9

A company wants to generate personalized product recommendations for each customer based on their purchase history and browsing behavior. Which approach is MOST appropriate?

Accepted Answer

Train a supervised learning model on historical purchase data to predict the next product a customer will buy. Supervised learning can predict what a customer might buy next based on labeled data (past purchases). Unsupervised learning can cluster customers but doesn't directly generate recommendations. Reinforcement learning is for dynamic environments, and generative AI creates content, not recommendations.

Answer

Use a generative AI model to create new product descriptions for each customer

Answer

Deploy a reinforcement learning agent that explores different recommendations in real-time

Answer

Use an unsupervised learning algorithm to cluster customers and recommend popular items in each cluster

Question 10

A financial services firm uses an AI model to approve loan applications. They discover that the model denies loans at a higher rate for a certain demographic group, even when financial indicators are similar. What is the primary ethical concern?

Accepted Answer

Bias in training data. Bias in training data leads to unfair outcomes for certain groups. This is a fairness and bias issue.

Answer

Low model accuracy

Answer

Model overfitting

Answer

Hallucination

Question 11

A sales manager wants to predict which deals are likely to close this quarter. The CRM has rich historical data on won/lost opportunities, deal amount, and sales stage. Which AI approach is best suited for this task?

Accepted Answer

Predictive AI for opportunity scoring. Predictive AI uses historical data to forecast outcomes, making it ideal for opportunity scoring.

Answer

Generative AI to create new sales content

Answer

Unsupervised learning to cluster opportunities

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Reinforcement learning for sales strategy

Question 12

A company uses an NLP model to detect customer intent from chat messages. The model correctly identifies 'billing question' 90% of the time for actual billing questions, but also flags many non-billing messages as billing (false positives). Which metric should the team prioritize to reduce false alarms?

Accepted Answer

Precision. Precision focuses on the proportion of positive identifications that are correct; improving precision reduces false positives.

Answer

Accuracy

Answer

F1 score

Answer

Recall

Question 13

An e-commerce company uses AI to provide product recommendations. The model suggests popular items but fails to personalize for individual users. Which type of learning could improve personalization?

Accepted Answer

Supervised learning. Supervised learning can use user purchase history as labels to predict what a specific user might buy, enabling personalization.

Answer

Generative AI

Answer

Unsupervised learning

Answer

Reinforcement learning

Question 14

A CRM team wants to predict the expected revenue from each opportunity. The data includes opportunity amount, close date, stage, and historical win rates. Which type of AI is best suited?

Accepted Answer

Predictive AI. Predictive AI uses historical data to forecast outcomes. Regression (a type of predictive AI) predicts a continuous value like revenue.

Answer

Unsupervised learning

Answer

Generative AI

Answer

Reinforcement learning

Question 15

An admin wants to use Einstein Activity Capture to automatically log emails and events to Salesforce. Which TWO considerations are important when setting up this feature?

Accepted Answer

Events (meetings) are automatically created as Salesforce events.. Einstein Activity Capture automatically creates Salesforce event records for meetings (events) that are synced from connected email and calendar systems, such as Outlook or Google Calendar. This eliminates the need for manual entry, as the feature captures calendar events and logs them as Salesforce events based on configured settings.

Answer

It requires a separate license for each integration user.

Answer

Users must manually forward emails to Salesforce.

Answer

It only works with Outlook, not Gmail.