AIAI case studies
AIAI · Put your knowledge to work in context.
The Artificial Intelligence Associate (AIAI) is an entry-level credential for people who need to work confidently with AI systems without building them from scratch. It suits business analysts, project and product staff, data-adjacent roles, IT generalists, and career changers who want a shared vocabulary and a practical grasp of how AI projects actually run. The exam spans eight domains: AI fundamentals and terminology; machine learning concepts and the model lifecycle; data preparation and data quality; generative AI and large language models; ethics, bias, and responsible AI; security, privacy, and governance; business use cases; and solution development and deployment. Expect multiple-choice questions that test judgment as much as definitions - recognizing an appropriate use case, spotting a data quality problem, or choosing a sensible governance control. The AIAI case studies are 5 cases and about 2,249 words.
1Loan Approval Model Bias and Fairness
A bank has deployed a machine learning model to approve or deny personal loans. The model was trained on 5 years of historical loan data.
422 words, about 2 min2LLM Hallucination in Customer Support
A telecommunications company deployed a large language model (LLM) to handle customer support chats. The LLM is fine-tuned on company documentation and past chat logs.
482 words, about 2 min3Data Quality Issues in Predictive Maintenance
A manufacturing plant uses sensors on critical machinery to predict failures. The data pipeline collects temperature, vibration, and pressure readings every minute.
448 words, about 2 min4Privacy-Preserving AI in Healthcare
A hospital wants to build an AI model to predict patient readmission risk using electronic health records (EHR). The EHR data includes sensitive information: patient names, addresses, dates of birth, diagnoses, medications, and lab results.
463 words, about 2 min5AI Security: Adversarial Attack on Image Classifier
A company uses an image classification model to detect defects in manufactured parts on an assembly line. The model achieves 98% accuracy on test data.
434 words, about 2 min