IBM Assessment: Foundations of AI Intermediate Practice Exam: Medium Difficulty 2025

A retail company wants to implement an AI system that can understand customer questions in natural language and provide relevant product recommendations. The system needs to handle ambiguous queries and learn from customer interactions over time. Which combination of AI technologies would be MOST appropriate for this solution?

A data scientist is building a supervised learning model to predict customer churn. After training the model on historical data, it achieves 95% accuracy on the training set but only 65% accuracy on the test set. What is the MOST likely problem, and what should be the primary remediation strategy?

An organization is developing an AI-powered hiring system to screen job applications. During testing, they discover that the system consistently ranks candidates from certain demographic groups lower than others, even when qualifications are similar. What is the PRIMARY ethical concern, and what should be the FIRST step to address it?

A manufacturing company wants to predict equipment failures before they occur using sensor data collected from machinery. They have labeled data for past failures and normal operations. Which type of machine learning approach and evaluation metric would be MOST appropriate for this scenario?

A healthcare application uses AI to analyze medical images and suggest potential diagnoses to radiologists. The development team needs to ensure the model's predictions can be understood and verified by medical professionals. Which AI principle is MOST critical here, and what implementation approach supports it?

A developer is building a chatbot application using a pre-trained large language model (LLM). The chatbot needs to answer questions specific to the company's internal policies and procedures. What is the MOST effective approach to customize the LLM for this specific use case?

During the data preparation phase for a machine learning project, a data scientist discovers that 30% of the values in a critical feature column are missing. The feature is strongly correlated with the target variable. What is the MOST appropriate strategy to handle this situation?

A financial services company is deploying an AI model that approves or denies loan applications. Regulatory requirements mandate that applicants must be able to understand why their application was denied. Which combination of practices BEST addresses this requirement?

A machine learning team is comparing different algorithms for a classification problem. Algorithm A achieves 92% accuracy, while Algorithm B achieves 88% accuracy. However, the dataset is imbalanced with 95% negative class and 5% positive class. What conclusion should the team draw?

An AI system deployed in production is being monitored for performance over time. The operations team notices that the model's accuracy has gradually decreased from 85% to 72% over six months, despite no changes to the model code. What is the MOST likely cause, and what should be done?