IBM A1000-068 Intermediate Practice Exam: Medium Difficulty 2025

A retail company wants to implement an AI system that can predict customer churn by analyzing purchase history, browsing behavior, and customer service interactions. Which type of machine learning approach would be most appropriate for this scenario?

An organization is designing an AI governance framework and needs to address potential bias in their hiring recommendation system. Which combination of practices would best support bias mitigation throughout the AI lifecycle?

A manufacturing company wants to use IBM Watson to analyze equipment sensor data and predict maintenance needs. They have structured data from IoT sensors and unstructured data from maintenance logs. Which IBM AI capability would be most suitable for combining these data sources to generate actionable insights?

A healthcare provider is implementing an AI system to assist radiologists in detecting anomalies in medical images. During testing, the system shows 95% accuracy on the training dataset but only 78% accuracy on real-world patient images. What is the most likely explanation and appropriate solution?

A financial services company wants to deploy an AI-powered loan approval system. According to AI ethics and governance best practices, which approach would best balance automation efficiency with regulatory compliance and fairness?

An e-commerce company wants to implement a recommendation system that suggests products to customers. They have millions of products and users. Which combination of AI techniques would be most effective for this large-scale scenario?

A company is using IBM Watson Natural Language Understanding to analyze customer feedback across multiple languages. They need to extract sentiment, emotions, and key topics from the text. What preprocessing consideration is most critical for ensuring accurate multilingual analysis?

A logistics company wants to optimize delivery routes in real-time based on traffic conditions, weather, and delivery priorities. Which AI approach would be most suitable for this dynamic, sequential decision-making problem?

A pharmaceutical company is implementing an AI system to accelerate drug discovery by analyzing molecular structures and predicting compound efficacy. Which combination of AI use case benefits and governance considerations is most important for this application?

An organization is evaluating their AI model's performance and needs to choose appropriate metrics. Their use case involves detecting fraudulent transactions where fraud represents only 2% of all transactions. Which evaluation approach would be most appropriate?